ShiftDesk v4: 79 tasks served, 53-task training list (32 new file-deliverable tasks), bash/write_file tools

README.md

@@ -8,49 +8,63 @@ configs:
       - split: train
         path: tasks.jsonl
 ---
-# ShiftDesk v3
+# ShiftDesk v4
 
-An OpenEnv environment for OpenEnv Arena. 47 tasks from 27 procedural families covering all eight arena
-domains (software 5, industrial 6, natural science 5, office 5, finance 7, math and formal reasoning 9,
-cybersecurity 5, media 5). Every reset generates a fresh instance (files, question, answer) from a seeded
-generator, so there are no fixed answer keys and this dataset holds none: `tasks.jsonl` lists each task id
-with a seed-0 example question, the answer format and the file names.
+An OpenEnv environment for OpenEnv Arena. v4 adds a terminal: a `bash` tool and a `write_file` tool next to
+`list_files`, `read_file` and `run_python`, a working directory that persists for the whole episode, and 32 new
+**file-deliverable** tasks (16 families x 2 levels) in the four domains where earlier versions never scored:
+natural science, math and formal reasoning, cybersecurity, and media. Each asks for a real output file
+(`output/results.csv`, `output/incident.json`, `output/out.srt`, `output/article.html`, ...) that hidden
+checks grade on submit. All 47 v3 answer-style tasks are still served.
+
+The training list (`in_training_list` in `tasks.jsonl`) has 53 tasks: the 32 new ones (60%) interleaved with
+21 v3 tasks from software, industrial, office and finance (40%), so the domains that already score keep training.
+Every reset generates a fresh instance from a seeded generator, so there are no fixed answer keys and this
+dataset holds none: `tasks.jsonl` lists each task id with a seed-0 example question, its deliverable path or
+answer format, and its file names.
 
 ## What the agent does
 
-Each episode is a small workspace of text files and four plain tools, listed with one example call each in the
-first observation:
+Each episode is a working directory with the task files and an empty `output/` folder. Tools, each shown with a
+one-line JSON example in the first observation:
 
-- `list_files` `{}`
+- `list_files` `{}`: everything in the working directory, including files the agent wrote
 - `read_file` `{"path": ..., "offset": optional first line}` (2,500 characters per call)
-- `run_python` `{"code": ...}` (Python 3 standard library, task files in the working directory, runs as `nobody`)
-- `submit` `{"answer": ...}` ends the episode
+- `write_file` `{"path": ..., "content": ...}`: create or overwrite a file inside the working directory
+- `bash` `{"command": ...}`: a shell with python3, grep, awk, sed, sort, jq, sqlite3, bc, openssl, file
+- `run_python` `{"code": ...}`: Python 3 with the standard library, numpy, sympy and PIL
+- `submit` `{"answer": ...}` ends the episode (for file tasks the answer can be empty)
 
-Answers are small JSON objects with named fields (for example `{"best_project": "P41", "npv": 18234.55}`).
+`bash` and `run_python` run as `nobody` with CPU, memory, file-size and process limits and a 20 s wall timeout;
+`write_file` writes through the same sandboxed child. Outbound IPv4/IPv6 sockets are refused by a seccomp
+filter. The instance salt and the server code are root-only.
 
-| Domain | Families (levels) |
+| Domain | New v4 file families (levels 1, 2) |
 |---|---|
-| Software engineering | change-impact (1,2): rebuild set and deterministic build order with dev-only edges; version-resolve (1,2): semver ranges, plugin constraints, yanked releases; module-repair (3) |
-| Industrial & physical | bom-explosion (1,2): BOM explosion with scrap and stock netting; tank-balance (1,2): level and alarm time with overflow and a tripped pump; line-oee (2,3) |
-| Natural science | beer-lambert (1,2): least-squares calibration with blank subtraction, an excluded standard, dilution; stoichiometry (1,2): limiting reagent, purity, process yield; kinetics-lab (3) |
-| Office & white-collar | meeting-slot (1,2): earliest common slot across time zones with a late calendar change; invoice-match (1,2): three-way match with tolerance and credit notes; expense-policy (3) |
-| Finance & economics | npv-choice (1,2): NPV by risk class with errata; bond-desk (1,2): price and modified duration; fifo-basis (1,2): FIFO realized gain with fees and a split; loan-desk (3) |
-| Math & formal reasoning | congruences (1,2): CRT with non-coprime moduli; logic-grid (1,2): unique-solution seating puzzles; shortest-route (1,2): closures and a waypoint; exact-probability (1,2): reduced fractions; exact-count (3) |
-| Cybersecurity | firewall-audit (1,2): first-match rules with an approved change; vuln-triage (1,2): numeric semver ranges and vendor backports; auth-hunt (3) |
-| Media & content | edit-timeline (1,2): EDL frames and timecode after review notes; headline-style (1,2): a two-page style guide; subtitle-qc (3) |
+| Natural science | assay-reduction: plate-reader calibration with mixed units, QC-flagged wells, replicates and out-of-range samples -> results.csv; peak-picking: spectrum peak table with baseline windows and cosmic-ray removal -> peaks.json; dilution-plan: direct and serial dilution plans from mg/mL stocks -> plan.csv; pk-fit: non-compartmental PK (AUC, k_el, half-life) with BLQ handling and clock-time sampling -> pk.json |
+| Math & formal reasoning | linear-system: exact rational solutions with a redundant and a voided equation -> solution.json; recurrence-id: smallest linear recurrence (with constant) and a far term mod p -> answer.json; claim-check: exhaustive checks with smallest counterexamples -> verdicts.json; board-expectation: exact expected turns of a dice game with exact-landing and bonus rolls -> answer.json |
+| Cybersecurity | web-forensics: nginx log attacker, UTC timeline and successful payloads in an unordered merged log -> incident.json; decode-chain: layered base64/hex/rot13/URL/XOR blobs and salted hash cracking -> decoded.json; sshd-audit: effective sshd_config (first value wins, defaults, Match blocks) against a baseline -> findings.json; jwt-inspect: HS256 verification with kid, exp/nbf, issuer, audience and a check order -> report.json |
+| Media & content | srt-retime: offset and two-point linear retiming with credit removal and renumbering -> out.srt; image-audit: real format, EXIF-rotated display size and extension checks -> report.csv; audio-audit: WAV duration, peak dBFS and clipping -> audio_report.csv; markdown-html: Markdown to house-style HTML (slug ids, demoted h1s, external-link attributes) -> article.html |
+
+v3 answer-style families (all still served): change-impact, version-resolve, module-repair (software);
+bom-explosion, tank-balance, line-oee (industrial); beer-lambert, stoichiometry, kinetics-lab (science);
+meeting-slot, invoice-match, expense-policy (office); npv-choice, bond-desk, fifo-basis, loan-desk (finance);
+congruences, logic-grid, shortest-route, exact-probability, exact-count (math); firewall-audit, vuln-triage,
+auth-hunt (security); edit-timeline, headline-style, subtitle-qc (media).
 
 ## What it is meant to teach
 
-General desk habits rather than one tool's quirks: read every file (level-2 tasks put a correction, errata,
-change log or second page in a separate file), compute with Python instead of by eye, and submit exactly the
-requested JSON fields. Tool names are conventional and fixed; there is no ritual end action.
+Terminal work the way held-out skills tasks are shaped: read every file (level 2 hides a caveat in a second file:
+QC flags, an SOP step, errata, a sync sheet, a style guide), compute with code instead of by eye, and leave a
+correctly formatted output file where the task asks for it.
 
 ## Reward
 
-All or nothing: 1.0 only when every requested field is right (numeric tolerances are stated in the answer
-format; ids, lists, versions and timecodes match exactly, lists in any order unless an order is asked for),
-otherwise 0.0. No answer, an empty answer, running out of calls, or an invalid reply scores 0.0. The finish
-action `{"tool": "submit", "args": {"answer": ""}}` scores 0.0.
+Binary. File tasks: 1.0 only when the deliverable exists at the requested path, is a regular file (symlinks are
+refused), parses, and passes every hidden check (stated numeric tolerances; ids, lists, timestamps and HTML
+structure exact); otherwise 0.0. The deliverable is graded on `submit`, on the finish action, and when calls run
+out. Answer tasks (v3): 1.0 only when every requested JSON field is right. The finish action
+`{"tool": "submit", "args": {"answer": ""}}` scores 0.0 unless the deliverable file is already correct.
 
 ## Same instance for a group
 
@@ -59,9 +73,11 @@ secret in the image), so the parallel rollouts of an optimizer step are compared
 
 ## Checks
 
-For every task over 100+ seeds: the reference answer scores 1 as an object and as a JSON string, plausible
-wrong answers (the answer you get by skipping the caveat file) and empty answers score 0, and generation is
-deterministic per seed. For all 19 new families an independent solver that reads only the question and files
-reproduces every label. `openenv validate` passes and every task replays to a terminal reward over WebSocket.
+For every task over 60+ seeds: the reference scores 1, plausible wrong outputs (what you get by skipping the
+caveat) and empty outputs score 0, and generation is deterministic per seed. For all 16 new families an
+independent solver that reads only the question and files plays full episodes through `write_file`, `bash` and
+`run_python` and earns 1 on every seed tried (150 seeds per task offline); an empty submit, the right content
+passed only as the answer, an empty file, a symlinked deliverable and a wrong file all earn 0. `openenv validate`
+passes and every task replays to a terminal reward over WebSocket with the new tools.
 
 Source: https://github.com/nice-bills/shiftdesk

tasks.jsonl

@@ -1,47 +1,79 @@
-{"task_id": "change-impact-L1", "domain": "software-engineering", "family": "change-impact", "level": 1, "budget_calls": 8, "example_question": "Which modules must be rebuilt, and in what order?", "answer_format": "a JSON object {\"rebuild\": [\"core\", \"web\"], \"build_order\": [\"core\", \"web\"]}", "files": ["BUILD.md", "change.txt", "modules.json"]}
-{"task_id": "change-impact-L2", "domain": "software-engineering", "family": "change-impact", "level": 2, "budget_calls": 8, "example_question": "Which modules must be rebuilt, and in what order?", "answer_format": "a JSON object {\"rebuild\": [\"core\", \"web\"], \"build_order\": [\"core\", \"web\"]}", "files": ["BUILD.md", "change.txt", "modules.json"]}
-{"task_id": "version-resolve-L1", "domain": "software-engineering", "family": "version-resolve", "level": 1, "budget_calls": 8, "example_question": "Resolve one version for each package in requirements.txt using registry.json.", "answer_format": "a JSON object mapping every package to a version string, e.g. {\"flask\": \"2.3.1\", \"axios\": \"none\"}", "files": ["RESOLVER.md", "registry.json", "requirements.txt"]}
-{"task_id": "version-resolve-L2", "domain": "software-engineering", "family": "version-resolve", "level": 2, "budget_calls": 8, "example_question": "Resolve one version for each package in requirements.txt using registry.json.", "answer_format": "a JSON object mapping every package to a version string, e.g. {\"flask\": \"2.3.1\", \"axios\": \"none\"}", "files": ["RESOLVER.md", "advisory.txt", "registry.json", "requirements.txt"]}
-{"task_id": "module-repair-L3", "domain": "software-engineering", "family": "module-repair", "level": 3, "budget_calls": 12, "example_question": "utils.py has 3 bugs (one per function at most). test_utils.py fails. Fix utils.py so every function matches its docstring. Hidden tests check every function against its docstring. The visible tests do not cover every bug. Submit the complete corrected contents of utils.py as the answer string.", "answer_format": "a string holding the whole fixed file, with newlines escaped as \\n inside the JSON string", "files": ["test_utils.py", "utils.py"]}
-{"task_id": "bom-explosion-L1", "domain": "industrial-physical-systems", "family": "bom-explosion", "level": 1, "budget_calls": 8, "example_question": "Explode the work order through bom.csv. How many units of each raw material are required?", "answer_format": "a JSON object mapping each raw material id to an integer, e.g. {\"RM-12\": 340, \"RM-40\": 95}", "files": ["bom.csv", "work_order.txt"]}
-{"task_id": "bom-explosion-L2", "domain": "industrial-physical-systems", "family": "bom-explosion", "level": 2, "budget_calls": 8, "example_question": "Explode the work order through bom.csv. How many units of each raw material are required to buy?", "answer_format": "a JSON object mapping each raw material id to an integer, e.g. {\"RM-12\": 340, \"RM-40\": 95}", "files": ["bom.csv", "stock.csv", "work_order.txt"]}
-{"task_id": "tank-balance-L1", "domain": "industrial-physical-systems", "family": "tank-balance", "level": 1, "budget_calls": 8, "example_question": "What is the tank level in litres at 11:35, and at what time (HH:MM, rounded up to the whole minute) does the level first reach the alarm level?", "answer_format": "a JSON object {\"final_level_l\": 7350, \"first_alarm\": \"08:47\"}", "files": ["flows.csv", "tank.txt"]}
-{"task_id": "tank-balance-L2", "domain": "industrial-physical-systems", "family": "tank-balance", "level": 2, "budget_calls": 8, "example_question": "What is the tank level in litres at 10:40, and at what time (HH:MM, rounded up to the whole minute) does the level first reach the alarm level?", "answer_format": "a JSON object {\"final_level_l\": 7350, \"first_alarm\": \"08:47\"}", "files": ["flows.csv", "shift_log.txt", "tank.txt"]}
-{"task_id": "line-oee-L2", "domain": "industrial-physical-systems", "family": "line-oee", "level": 2, "budget_calls": 10, "example_question": "What was the OEE of machine M58 this shift, in percent? Round to 1 decimal.", "answer_format": "a number such as 61.2", "files": ["notes.txt", "production.csv", "states.csv"]}
-{"task_id": "line-oee-L3", "domain": "industrial-physical-systems", "family": "line-oee", "level": 3, "budget_calls": 12, "example_question": "Which machine had the lowest OEE this shift, and what was it? Answer as the machine id, a space, and the OEE percent rounded to 1 decimal.", "answer_format": "a string such as \"M17 54.3\"", "files": ["notes.txt", "production.csv", "states.csv"]}
-{"task_id": "beer-lambert-L1", "domain": "natural-science", "family": "beer-lambert", "level": 1, "budget_calls": 10, "example_question": "Using the calibration standards, find the fitted slope (AU per uM) and the original concentration of sample U3 in uM.", "answer_format": "a JSON object {\"slope\": 0.012345, \"concentration_uM\": 41.27} (within 0.5%)", "files": ["notebook.txt", "samples.csv", "standards.csv"]}
-{"task_id": "beer-lambert-L2", "domain": "natural-science", "family": "beer-lambert", "level": 2, "budget_calls": 10, "example_question": "Using the calibration standards, find the fitted slope (AU per uM) and the original concentration of sample U5 in uM.", "answer_format": "a JSON object {\"slope\": 0.012345, \"concentration_uM\": 41.27} (within 0.5%)", "files": ["notebook.txt", "samples.csv", "standards.csv"]}
-{"task_id": "stoichiometry-L1", "domain": "natural-science", "family": "stoichiometry", "level": 1, "budget_calls": 8, "example_question": "Which reactant limits the batch, and what mass of Na2SO4 do you expect in theory? Use atomic_masses.txt for molar masses.", "answer_format": "a JSON object {\"limiting\": \"<formula>\", \"theoretical_g\": 12.34} (mass in grams, within 0.5%)", "files": ["atomic_masses.txt", "batch.txt"]}
-{"task_id": "stoichiometry-L2", "domain": "natural-science", "family": "stoichiometry", "level": 2, "budget_calls": 8, "example_question": "Which reactant limits the batch, and what mass of Na2SO4 do you expect to isolate? Use atomic_masses.txt for molar masses.", "answer_format": "a JSON object {\"limiting\": \"<formula>\", \"expected_g\": 12.34} (mass in grams, within 0.5%)", "files": ["atomic_masses.txt", "batch.txt"]}
-{"task_id": "kinetics-lab-L3", "domain": "natural-science", "family": "kinetics-lab", "level": 3, "budget_calls": 12, "example_question": "From run.csv and protocol.txt: what is the reaction order and the half-life in minutes? Answer as the order, a space, and the half-life to 4 significant figures.", "answer_format": "a string such as \"1 23.45\"", "files": ["protocol.txt", "run.csv"]}
-{"task_id": "meeting-slot-L1", "domain": "office-white-collar", "family": "meeting-slot", "level": 1, "budget_calls": 8, "example_question": "Find the earliest start time for the call, in UTC (HH:MM).", "answer_format": "a JSON object {\"start_utc\": \"13:15\"}", "files": ["calendars.csv", "request.txt"]}
-{"task_id": "meeting-slot-L2", "domain": "office-white-collar", "family": "meeting-slot", "level": 2, "budget_calls": 8, "example_question": "Find the earliest start time for the call, in UTC (HH:MM).", "answer_format": "a JSON object {\"start_utc\": \"13:15\"}", "files": ["calendars.csv", "inbox.txt", "request.txt"]}
-{"task_id": "invoice-match-L1", "domain": "office-white-collar", "family": "invoice-match", "level": 1, "budget_calls": 8, "example_question": "Which invoices can be approved under ap_policy.txt, and what is the total payable for them?", "answer_format": "a JSON object {\"approved\": [\"INV-12345\"], \"total\": 1234.56}", "files": ["ap_policy.txt", "invoices.csv", "purchase_orders.csv", "receipts.csv"]}
-{"task_id": "invoice-match-L2", "domain": "office-white-collar", "family": "invoice-match", "level": 2, "budget_calls": 8, "example_question": "Which invoices can be approved under ap_policy.txt, and what is the total payable for them?", "answer_format": "a JSON object {\"approved\": [\"INV-12345\"], \"total\": 1234.56}", "files": ["ap_policy.txt", "credit_notes.csv", "invoices.csv", "purchase_orders.csv", "receipts.csv"]}
-{"task_id": "expense-policy-L3", "domain": "office-white-collar", "family": "expense-policy", "level": 3, "budget_calls": 12, "example_question": "Using expenses.csv and policy.md, how much should Lena Weiss be reimbursed in USD for 2026-04? Round to cents.", "answer_format": "a number such as 812.40", "files": ["expenses.csv", "policy.md", "rates.txt"]}
-{"task_id": "npv-choice-L1", "domain": "finance-economics", "family": "npv-choice", "level": 1, "budget_calls": 8, "example_question": "Which project has the highest net present value, and what is that NPV in USD?", "answer_format": "a JSON object {\"best_project\": \"P00\", \"npv\": 123456.78} (NPV within 1 USD)", "files": ["memo.txt", "projects.csv"]}
-{"task_id": "npv-choice-L2", "domain": "finance-economics", "family": "npv-choice", "level": 2, "budget_calls": 8, "example_question": "Which project has the highest net present value, and what is that NPV in USD?", "answer_format": "a JSON object {\"best_project\": \"P00\", \"npv\": 123456.78} (NPV within 1 USD)", "files": ["memo.txt", "projects.csv"]}
-{"task_id": "bond-desk-L1", "domain": "finance-economics", "family": "bond-desk", "level": 1, "budget_calls": 8, "example_question": "What is the price of bond BD323 per its full face value?", "answer_format": "a JSON object {\"price\": 101.2345} (within 0.01 per 100 face)", "files": ["bonds.csv", "conventions.txt"]}
-{"task_id": "bond-desk-L2", "domain": "finance-economics", "family": "bond-desk", "level": 2, "budget_calls": 8, "example_question": "For bond BD323, give its price per full face value and its modified duration in years.", "answer_format": "a JSON object {\"price\": 101.2345, \"modified_duration\": 4.5678} (price within 0.01 per 100 face, duration within 0.005)", "files": ["bonds.csv", "conventions.txt"]}
-{"task_id": "fifo-basis-L1", "domain": "finance-economics", "family": "fifo-basis", "level": 1, "budget_calls": 8, "example_question": "For NOVA only: what is the total realized gain (USD) and how many shares are still held?", "answer_format": "a JSON object {\"realized_gain\": -123.45, \"shares_held\": 40} (gain within 0.02)", "files": ["policy.txt", "trades.csv"]}
-{"task_id": "fifo-basis-L2", "domain": "finance-economics", "family": "fifo-basis", "level": 2, "budget_calls": 8, "example_question": "For KORA only: what is the total realized gain (USD) and how many shares are still held?", "answer_format": "a JSON object {\"realized_gain\": -123.45, \"shares_held\": 40} (gain within 0.02)", "files": ["policy.txt", "trades.csv"]}
-{"task_id": "loan-desk-L3", "domain": "finance-economics", "family": "loan-desk", "level": 3, "budget_calls": 12, "example_question": "Use loans.csv and rules.txt. With the extra payments, how much total interest is paid on loan LN-4578 until it is fully repaid? Dollars, rounded to cents.", "answer_format": "a number such as 12345.67", "files": ["loans.csv", "rules.txt"]}
-{"task_id": "congruences-L1", "domain": "mathematics-or-formal-reasoning", "family": "congruences", "level": 1, "budget_calls": 6, "example_question": "system.txt lists a system of congruences. Give the smallest non-negative solution x and the modulus M such that the solutions are exactly x + k*M.", "answer_format": "a JSON object {\"x\": 1234, \"modulus\": 5040} with integers", "files": ["system.txt"]}
-{"task_id": "congruences-L2", "domain": "mathematics-or-formal-reasoning", "family": "congruences", "level": 2, "budget_calls": 6, "example_question": "system.txt lists a system of congruences. Give the smallest non-negative solution x and the modulus M such that the solutions are exactly x + k*M, and the count it asks for.", "answer_format": "a JSON object {\"x\": 1234, \"modulus\": 5040, \"count_in_range\": 7} with integers", "files": ["system.txt"]}
-{"task_id": "logic-grid-L1", "domain": "mathematics-or-formal-reasoning", "family": "logic-grid", "level": 1, "budget_calls": 8, "example_question": "Solve the puzzle in puzzle.txt. Give each person's city.", "answer_format": "a JSON object mapping every person to a value, e.g. {\"Goran\": \"Quito\", ...}", "files": ["puzzle.txt"]}
-{"task_id": "logic-grid-L2", "domain": "mathematics-or-formal-reasoning", "family": "logic-grid", "level": 2, "budget_calls": 8, "example_question": "Solve the puzzle in puzzle.txt. Give each person's pet.", "answer_format": "a JSON object mapping every person to a value, e.g. {\"Goran\": \"cat\", ...}", "files": ["puzzle.txt"]}
-{"task_id": "shortest-route-L1", "domain": "mathematics-or-formal-reasoning", "family": "shortest-route", "level": 1, "budget_calls": 8, "example_question": "Roads in roads.csv are two-way. Find the fastest route from J to G. Give the total minutes and the route as a list of nodes, start and end included.", "answer_format": "a JSON object {\"minutes\": 37, \"route\": [\"A\", \"D\", \"C\"]}", "files": ["roads.csv"]}
-{"task_id": "shortest-route-L2", "domain": "mathematics-or-formal-reasoning", "family": "shortest-route", "level": 2, "budget_calls": 8, "example_question": "Roads in roads.csv are two-way. Find the fastest route from D to E that passes through I, avoiding closed roads (see notice.txt). Give the total minutes and the route as a list of nodes, start and end included.", "answer_format": "a JSON object {\"minutes\": 37, \"route\": [\"A\", \"D\", \"C\"]}", "files": ["notice.txt", "roads.csv"]}
-{"task_id": "exact-probability-L1", "domain": "mathematics-or-formal-reasoning", "family": "exact-probability", "level": 1, "budget_calls": 6, "example_question": "Answer the question in problem.txt as an exact reduced fraction.", "answer_format": "a JSON object {\"probability\": \"a/b\"} with the fraction in lowest terms", "files": ["problem.txt"]}
-{"task_id": "exact-probability-L2", "domain": "mathematics-or-formal-reasoning", "family": "exact-probability", "level": 2, "budget_calls": 6, "example_question": "Answer the question in problem.txt as an exact reduced fraction.", "answer_format": "a JSON object {\"probability\": \"a/b\"} with the fraction in lowest terms", "files": ["problem.txt"]}
-{"task_id": "exact-count-L3", "domain": "mathematics-or-formal-reasoning", "family": "exact-count", "level": 3, "budget_calls": 8, "example_question": "Count the 49-digit positive integers (no leading zero) whose digits sum to 292 and that never use the digit 6. Give the count modulo 1000000007.", "answer_format": "an integer", "files": []}
-{"task_id": "firewall-audit-L1", "domain": "cybersecurity", "family": "firewall-audit", "level": 1, "budget_calls": 8, "example_question": "Which packets in packets.csv does the live firewall allow?", "answer_format": "a JSON object {\"allowed\": [\"P01\", \"P07\"]} listing every allowed packet id", "files": ["packets.csv", "rules.txt"]}
-{"task_id": "firewall-audit-L2", "domain": "cybersecurity", "family": "firewall-audit", "level": 2, "budget_calls": 8, "example_question": "Which packets in packets.csv does the live firewall allow? Apply change_log.txt to rules.txt first.", "answer_format": "a JSON object {\"allowed\": [\"P01\", \"P07\"]} listing every allowed packet id", "files": ["change_log.txt", "packets.csv", "rules.txt"]}
-{"task_id": "vuln-triage-L1", "domain": "cybersecurity", "family": "vuln-triage", "level": 1, "budget_calls": 8, "example_question": "Versions are semantic (major.minor.patch, compared numerically). Which hosts run at least one package version covered by an advisory? Also give how many hosts that is.", "answer_format": "a JSON object {\"hosts\": [\"app-03\", \"web-01\"], \"count\": 2}", "files": ["advisories.json", "inventory.csv"]}
-{"task_id": "vuln-triage-L2", "domain": "cybersecurity", "family": "vuln-triage", "level": 2, "budget_calls": 8, "example_question": "Versions are semantic (major.minor.patch, compared numerically). Which hosts run at least one package version covered by an advisory? Also give how many hosts that is.", "answer_format": "a JSON object {\"hosts\": [\"app-03\", \"web-01\"], \"count\": 2}", "files": ["advisories.json", "inventory.csv", "vendor_notes.txt"]}
-{"task_id": "auth-hunt-L3", "domain": "cybersecurity", "family": "auth-hunt", "level": 3, "budget_calls": 12, "example_question": "An attacker rotated source addresses inside one /24 network. Treat all IPs in the same /24 as one source. Find the /24 with at least 5 failed passwords for one user within any 10-minute span, followed within 10 minutes of its last failure by an accepted login for that same user from the same /24. Answer in CIDR form, like 198.51.100.0/24. The log is auth.log.", "answer_format": "a string", "files": ["auth.log"]}
-{"task_id": "edit-timeline-L1", "domain": "media-content-production", "family": "edit-timeline", "level": 1, "budget_calls": 8, "example_question": "Clips play back to back in the listed order. What is the total program length in frames, and as a timecode HH:MM:SS:FF at the timeline frame rate?", "answer_format": "a JSON object {\"frames\": 4321, \"timecode\": \"00:02:52:21\"}", "files": ["timeline.edl"]}
-{"task_id": "edit-timeline-L2", "domain": "media-content-production", "family": "edit-timeline", "level": 2, "budget_calls": 8, "example_question": "After applying review_notes.txt: clips play back to back in the listed order. What is the total program length in frames, and as a timecode HH:MM:SS:FF at the timeline frame rate?", "answer_format": "a JSON object {\"frames\": 4321, \"timecode\": \"00:02:52:21\"}", "files": ["review_notes.txt", "timeline.edl"]}
-{"task_id": "headline-style-L1", "domain": "media-content-production", "family": "headline-style", "level": 1, "budget_calls": 8, "example_question": "Which headlines in headlines.tsv break the house style guide? Read every page of the guide.", "answer_format": "a JSON object {\"violations\": [\"H02\", \"H09\"]} listing every breaking headline id", "files": ["headlines.tsv", "style_guide_p1.txt"]}
-{"task_id": "headline-style-L2", "domain": "media-content-production", "family": "headline-style", "level": 2, "budget_calls": 8, "example_question": "Which headlines in headlines.tsv break the house style guide? Read every page of the guide.", "answer_format": "a JSON object {\"violations\": [\"H02\", \"H09\"]} listing every breaking headline id", "files": ["headlines.tsv", "style_guide_p1.txt", "style_guide_p2.txt"]}
-{"task_id": "subtitle-qc-L3", "domain": "media-content-production", "family": "subtitle-qc", "level": 3, "budget_calls": 12, "example_question": "Check episode.srt against style.txt. Which cue numbers break the reading-speed rule? Answer with the cue numbers in increasing order, separated by commas (empty string if none).", "answer_format": "a string such as \"3,8,15\"", "files": ["episode.srt", "style.txt"]}
+{"task_id": "change-impact-L1", "domain": "software-engineering", "family": "change-impact", "level": 1, "budget_calls": 8, "example_question": "Which modules must be rebuilt, and in what order?", "answer_format": "a JSON object {\"rebuild\": [\"core\", \"web\"], \"build_order\": [\"core\", \"web\"]}", "files": ["BUILD.md", "change.txt", "modules.json"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "change-impact-L2", "domain": "software-engineering", "family": "change-impact", "level": 2, "budget_calls": 8, "example_question": "Which modules must be rebuilt, and in what order?", "answer_format": "a JSON object {\"rebuild\": [\"core\", \"web\"], \"build_order\": [\"core\", \"web\"]}", "files": ["BUILD.md", "change.txt", "modules.json"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "version-resolve-L1", "domain": "software-engineering", "family": "version-resolve", "level": 1, "budget_calls": 8, "example_question": "Resolve one version for each package in requirements.txt using registry.json.", "answer_format": "a JSON object mapping every package to a version string, e.g. {\"flask\": \"2.3.1\", \"axios\": \"none\"}", "files": ["RESOLVER.md", "registry.json", "requirements.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "version-resolve-L2", "domain": "software-engineering", "family": "version-resolve", "level": 2, "budget_calls": 8, "example_question": "Resolve one version for each package in requirements.txt using registry.json.", "answer_format": "a JSON object mapping every package to a version string, e.g. {\"flask\": \"2.3.1\", \"axios\": \"none\"}", "files": ["RESOLVER.md", "advisory.txt", "registry.json", "requirements.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "module-repair-L3", "domain": "software-engineering", "family": "module-repair", "level": 3, "budget_calls": 12, "example_question": "utils.py has 3 bugs (one per function at most). test_utils.py fails. Fix utils.py so every function matches its docstring. Hidden tests check every function against its docstring. The visible tests do not cover every bug. Submit the complete corrected contents of utils.py as the answer string.", "answer_format": "a string holding the whole fixed file, with newlines escaped as \\n inside the JSON string", "files": ["test_utils.py", "utils.py"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "bom-explosion-L1", "domain": "industrial-physical-systems", "family": "bom-explosion", "level": 1, "budget_calls": 8, "example_question": "Explode the work order through bom.csv. How many units of each raw material are required?", "answer_format": "a JSON object mapping each raw material id to an integer, e.g. {\"RM-12\": 340, \"RM-40\": 95}", "files": ["bom.csv", "work_order.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "bom-explosion-L2", "domain": "industrial-physical-systems", "family": "bom-explosion", "level": 2, "budget_calls": 8, "example_question": "Explode the work order through bom.csv. How many units of each raw material are required to buy?", "answer_format": "a JSON object mapping each raw material id to an integer, e.g. {\"RM-12\": 340, \"RM-40\": 95}", "files": ["bom.csv", "stock.csv", "work_order.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "tank-balance-L1", "domain": "industrial-physical-systems", "family": "tank-balance", "level": 1, "budget_calls": 8, "example_question": "What is the tank level in litres at 11:35, and at what time (HH:MM, rounded up to the whole minute) does the level first reach the alarm level?", "answer_format": "a JSON object {\"final_level_l\": 7350, \"first_alarm\": \"08:47\"}", "files": ["flows.csv", "tank.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "tank-balance-L2", "domain": "industrial-physical-systems", "family": "tank-balance", "level": 2, "budget_calls": 8, "example_question": "What is the tank level in litres at 10:40, and at what time (HH:MM, rounded up to the whole minute) does the level first reach the alarm level?", "answer_format": "a JSON object {\"final_level_l\": 7350, \"first_alarm\": \"08:47\"}", "files": ["flows.csv", "shift_log.txt", "tank.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "line-oee-L2", "domain": "industrial-physical-systems", "family": "line-oee", "level": 2, "budget_calls": 10, "example_question": "What was the OEE of machine M58 this shift, in percent? Round to 1 decimal.", "answer_format": "a number such as 61.2", "files": ["notes.txt", "production.csv", "states.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "line-oee-L3", "domain": "industrial-physical-systems", "family": "line-oee", "level": 3, "budget_calls": 12, "example_question": "Which machine had the lowest OEE this shift, and what was it? Answer as the machine id, a space, and the OEE percent rounded to 1 decimal.", "answer_format": "a string such as \"M17 54.3\"", "files": ["notes.txt", "production.csv", "states.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "beer-lambert-L1", "domain": "natural-science", "family": "beer-lambert", "level": 1, "budget_calls": 10, "example_question": "Using the calibration standards, find the fitted slope (AU per uM) and the original concentration of sample U3 in uM.", "answer_format": "a JSON object {\"slope\": 0.012345, \"concentration_uM\": 41.27} (within 0.5%)", "files": ["notebook.txt", "samples.csv", "standards.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "beer-lambert-L2", "domain": "natural-science", "family": "beer-lambert", "level": 2, "budget_calls": 10, "example_question": "Using the calibration standards, find the fitted slope (AU per uM) and the original concentration of sample U5 in uM.", "answer_format": "a JSON object {\"slope\": 0.012345, \"concentration_uM\": 41.27} (within 0.5%)", "files": ["notebook.txt", "samples.csv", "standards.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "stoichiometry-L1", "domain": "natural-science", "family": "stoichiometry", "level": 1, "budget_calls": 8, "example_question": "Which reactant limits the batch, and what mass of Na2SO4 do you expect in theory? Use atomic_masses.txt for molar masses.", "answer_format": "a JSON object {\"limiting\": \"<formula>\", \"theoretical_g\": 12.34} (mass in grams, within 0.5%)", "files": ["atomic_masses.txt", "batch.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "stoichiometry-L2", "domain": "natural-science", "family": "stoichiometry", "level": 2, "budget_calls": 8, "example_question": "Which reactant limits the batch, and what mass of Na2SO4 do you expect to isolate? Use atomic_masses.txt for molar masses.", "answer_format": "a JSON object {\"limiting\": \"<formula>\", \"expected_g\": 12.34} (mass in grams, within 0.5%)", "files": ["atomic_masses.txt", "batch.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "kinetics-lab-L3", "domain": "natural-science", "family": "kinetics-lab", "level": 3, "budget_calls": 12, "example_question": "From run.csv and protocol.txt: what is the reaction order and the half-life in minutes? Answer as the order, a space, and the half-life to 4 significant figures.", "answer_format": "a string such as \"1 23.45\"", "files": ["protocol.txt", "run.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "meeting-slot-L1", "domain": "office-white-collar", "family": "meeting-slot", "level": 1, "budget_calls": 8, "example_question": "Find the earliest start time for the call, in UTC (HH:MM).", "answer_format": "a JSON object {\"start_utc\": \"13:15\"}", "files": ["calendars.csv", "request.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "meeting-slot-L2", "domain": "office-white-collar", "family": "meeting-slot", "level": 2, "budget_calls": 8, "example_question": "Find the earliest start time for the call, in UTC (HH:MM).", "answer_format": "a JSON object {\"start_utc\": \"13:15\"}", "files": ["calendars.csv", "inbox.txt", "request.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "invoice-match-L1", "domain": "office-white-collar", "family": "invoice-match", "level": 1, "budget_calls": 8, "example_question": "Which invoices can be approved under ap_policy.txt, and what is the total payable for them?", "answer_format": "a JSON object {\"approved\": [\"INV-12345\"], \"total\": 1234.56}", "files": ["ap_policy.txt", "invoices.csv", "purchase_orders.csv", "receipts.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "invoice-match-L2", "domain": "office-white-collar", "family": "invoice-match", "level": 2, "budget_calls": 8, "example_question": "Which invoices can be approved under ap_policy.txt, and what is the total payable for them?", "answer_format": "a JSON object {\"approved\": [\"INV-12345\"], \"total\": 1234.56}", "files": ["ap_policy.txt", "credit_notes.csv", "invoices.csv", "purchase_orders.csv", "receipts.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "expense-policy-L3", "domain": "office-white-collar", "family": "expense-policy", "level": 3, "budget_calls": 12, "example_question": "Using expenses.csv and policy.md, how much should Lena Weiss be reimbursed in USD for 2026-04? Round to cents.", "answer_format": "a number such as 812.40", "files": ["expenses.csv", "policy.md", "rates.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "npv-choice-L1", "domain": "finance-economics", "family": "npv-choice", "level": 1, "budget_calls": 8, "example_question": "Which project has the highest net present value, and what is that NPV in USD?", "answer_format": "a JSON object {\"best_project\": \"P00\", \"npv\": 123456.78} (NPV within 1 USD)", "files": ["memo.txt", "projects.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "npv-choice-L2", "domain": "finance-economics", "family": "npv-choice", "level": 2, "budget_calls": 8, "example_question": "Which project has the highest net present value, and what is that NPV in USD?", "answer_format": "a JSON object {\"best_project\": \"P00\", \"npv\": 123456.78} (NPV within 1 USD)", "files": ["memo.txt", "projects.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "bond-desk-L1", "domain": "finance-economics", "family": "bond-desk", "level": 1, "budget_calls": 8, "example_question": "What is the price of bond BD323 per its full face value?", "answer_format": "a JSON object {\"price\": 101.2345} (within 0.01 per 100 face)", "files": ["bonds.csv", "conventions.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "bond-desk-L2", "domain": "finance-economics", "family": "bond-desk", "level": 2, "budget_calls": 8, "example_question": "For bond BD323, give its price per full face value and its modified duration in years.", "answer_format": "a JSON object {\"price\": 101.2345, \"modified_duration\": 4.5678} (price within 0.01 per 100 face, duration within 0.005)", "files": ["bonds.csv", "conventions.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "fifo-basis-L1", "domain": "finance-economics", "family": "fifo-basis", "level": 1, "budget_calls": 8, "example_question": "For NOVA only: what is the total realized gain (USD) and how many shares are still held?", "answer_format": "a JSON object {\"realized_gain\": -123.45, \"shares_held\": 40} (gain within 0.02)", "files": ["policy.txt", "trades.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "fifo-basis-L2", "domain": "finance-economics", "family": "fifo-basis", "level": 2, "budget_calls": 8, "example_question": "For KORA only: what is the total realized gain (USD) and how many shares are still held?", "answer_format": "a JSON object {\"realized_gain\": -123.45, \"shares_held\": 40} (gain within 0.02)", "files": ["policy.txt", "trades.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "loan-desk-L3", "domain": "finance-economics", "family": "loan-desk", "level": 3, "budget_calls": 12, "example_question": "Use loans.csv and rules.txt. With the extra payments, how much total interest is paid on loan LN-4578 until it is fully repaid? Dollars, rounded to cents.", "answer_format": "a number such as 12345.67", "files": ["loans.csv", "rules.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": true}
+{"task_id": "congruences-L1", "domain": "mathematics-or-formal-reasoning", "family": "congruences", "level": 1, "budget_calls": 6, "example_question": "system.txt lists a system of congruences. Give the smallest non-negative solution x and the modulus M such that the solutions are exactly x + k*M.", "answer_format": "a JSON object {\"x\": 1234, \"modulus\": 5040} with integers", "files": ["system.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "congruences-L2", "domain": "mathematics-or-formal-reasoning", "family": "congruences", "level": 2, "budget_calls": 6, "example_question": "system.txt lists a system of congruences. Give the smallest non-negative solution x and the modulus M such that the solutions are exactly x + k*M, and the count it asks for.", "answer_format": "a JSON object {\"x\": 1234, \"modulus\": 5040, \"count_in_range\": 7} with integers", "files": ["system.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "logic-grid-L1", "domain": "mathematics-or-formal-reasoning", "family": "logic-grid", "level": 1, "budget_calls": 8, "example_question": "Solve the puzzle in puzzle.txt. Give each person's city.", "answer_format": "a JSON object mapping every person to a value, e.g. {\"Goran\": \"Quito\", ...}", "files": ["puzzle.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "logic-grid-L2", "domain": "mathematics-or-formal-reasoning", "family": "logic-grid", "level": 2, "budget_calls": 8, "example_question": "Solve the puzzle in puzzle.txt. Give each person's pet.", "answer_format": "a JSON object mapping every person to a value, e.g. {\"Goran\": \"cat\", ...}", "files": ["puzzle.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "shortest-route-L1", "domain": "mathematics-or-formal-reasoning", "family": "shortest-route", "level": 1, "budget_calls": 8, "example_question": "Roads in roads.csv are two-way. Find the fastest route from J to G. Give the total minutes and the route as a list of nodes, start and end included.", "answer_format": "a JSON object {\"minutes\": 37, \"route\": [\"A\", \"D\", \"C\"]}", "files": ["roads.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "shortest-route-L2", "domain": "mathematics-or-formal-reasoning", "family": "shortest-route", "level": 2, "budget_calls": 8, "example_question": "Roads in roads.csv are two-way. Find the fastest route from D to E that passes through I, avoiding closed roads (see notice.txt). Give the total minutes and the route as a list of nodes, start and end included.", "answer_format": "a JSON object {\"minutes\": 37, \"route\": [\"A\", \"D\", \"C\"]}", "files": ["notice.txt", "roads.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "exact-probability-L1", "domain": "mathematics-or-formal-reasoning", "family": "exact-probability", "level": 1, "budget_calls": 6, "example_question": "Answer the question in problem.txt as an exact reduced fraction.", "answer_format": "a JSON object {\"probability\": \"a/b\"} with the fraction in lowest terms", "files": ["problem.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "exact-probability-L2", "domain": "mathematics-or-formal-reasoning", "family": "exact-probability", "level": 2, "budget_calls": 6, "example_question": "Answer the question in problem.txt as an exact reduced fraction.", "answer_format": "a JSON object {\"probability\": \"a/b\"} with the fraction in lowest terms", "files": ["problem.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "exact-count-L3", "domain": "mathematics-or-formal-reasoning", "family": "exact-count", "level": 3, "budget_calls": 8, "example_question": "Count the 49-digit positive integers (no leading zero) whose digits sum to 292 and that never use the digit 6. Give the count modulo 1000000007.", "answer_format": "an integer", "files": [], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "firewall-audit-L1", "domain": "cybersecurity", "family": "firewall-audit", "level": 1, "budget_calls": 8, "example_question": "Which packets in packets.csv does the live firewall allow?", "answer_format": "a JSON object {\"allowed\": [\"P01\", \"P07\"]} listing every allowed packet id", "files": ["packets.csv", "rules.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "firewall-audit-L2", "domain": "cybersecurity", "family": "firewall-audit", "level": 2, "budget_calls": 8, "example_question": "Which packets in packets.csv does the live firewall allow? Apply change_log.txt to rules.txt first.", "answer_format": "a JSON object {\"allowed\": [\"P01\", \"P07\"]} listing every allowed packet id", "files": ["change_log.txt", "packets.csv", "rules.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "vuln-triage-L1", "domain": "cybersecurity", "family": "vuln-triage", "level": 1, "budget_calls": 8, "example_question": "Versions are semantic (major.minor.patch, compared numerically). Which hosts run at least one package version covered by an advisory? Also give how many hosts that is.", "answer_format": "a JSON object {\"hosts\": [\"app-03\", \"web-01\"], \"count\": 2}", "files": ["advisories.json", "inventory.csv"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "vuln-triage-L2", "domain": "cybersecurity", "family": "vuln-triage", "level": 2, "budget_calls": 8, "example_question": "Versions are semantic (major.minor.patch, compared numerically). Which hosts run at least one package version covered by an advisory? Also give how many hosts that is.", "answer_format": "a JSON object {\"hosts\": [\"app-03\", \"web-01\"], \"count\": 2}", "files": ["advisories.json", "inventory.csv", "vendor_notes.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "auth-hunt-L3", "domain": "cybersecurity", "family": "auth-hunt", "level": 3, "budget_calls": 12, "example_question": "An attacker rotated source addresses inside one /24 network. Treat all IPs in the same /24 as one source. Find the /24 with at least 5 failed passwords for one user within any 10-minute span, followed within 10 minutes of its last failure by an accepted login for that same user from the same /24. Answer in CIDR form, like 198.51.100.0/24. The log is auth.log.", "answer_format": "a string", "files": ["auth.log"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "edit-timeline-L1", "domain": "media-content-production", "family": "edit-timeline", "level": 1, "budget_calls": 8, "example_question": "Clips play back to back in the listed order. What is the total program length in frames, and as a timecode HH:MM:SS:FF at the timeline frame rate?", "answer_format": "a JSON object {\"frames\": 4321, \"timecode\": \"00:02:52:21\"}", "files": ["timeline.edl"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "edit-timeline-L2", "domain": "media-content-production", "family": "edit-timeline", "level": 2, "budget_calls": 8, "example_question": "After applying review_notes.txt: clips play back to back in the listed order. What is the total program length in frames, and as a timecode HH:MM:SS:FF at the timeline frame rate?", "answer_format": "a JSON object {\"frames\": 4321, \"timecode\": \"00:02:52:21\"}", "files": ["review_notes.txt", "timeline.edl"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "headline-style-L1", "domain": "media-content-production", "family": "headline-style", "level": 1, "budget_calls": 8, "example_question": "Which headlines in headlines.tsv break the house style guide? Read every page of the guide.", "answer_format": "a JSON object {\"violations\": [\"H02\", \"H09\"]} listing every breaking headline id", "files": ["headlines.tsv", "style_guide_p1.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "headline-style-L2", "domain": "media-content-production", "family": "headline-style", "level": 2, "budget_calls": 8, "example_question": "Which headlines in headlines.tsv break the house style guide? Read every page of the guide.", "answer_format": "a JSON object {\"violations\": [\"H02\", \"H09\"]} listing every breaking headline id", "files": ["headlines.tsv", "style_guide_p1.txt", "style_guide_p2.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "subtitle-qc-L3", "domain": "media-content-production", "family": "subtitle-qc", "level": 3, "budget_calls": 12, "example_question": "Check episode.srt against style.txt. Which cue numbers break the reading-speed rule? Answer with the cue numbers in increasing order, separated by commas (empty string if none).", "answer_format": "a string such as \"3,8,15\"", "files": ["episode.srt", "style.txt"], "deliverable": null, "style": "answer", "new_in_v4": false, "in_training_list": false}
+{"task_id": "assay-reduction-L1", "domain": "natural-science", "family": "assay-reduction", "level": 1, "budget_calls": 16, "example_question": "Reduce the protein assay in plate.csv following protocol.md and write output/results.csv with columns sample_id,conc_mg_per_L (one row per sample, original undiluted concentration).", "answer_format": "output/results.csv", "files": ["plate.csv", "protocol.md"], "deliverable": "output/results.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "assay-reduction-L2", "domain": "natural-science", "family": "assay-reduction", "level": 2, "budget_calls": 20, "example_question": "Reduce the protein assay in plate.csv following every step of protocol.md and write output/results.csv with columns sample_id,conc_mg_per_L,status (one row per sample).", "answer_format": "output/results.csv", "files": ["plate.csv", "protocol.md", "qc_flags.txt"], "deliverable": "output/results.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "peak-picking-L1", "domain": "natural-science", "family": "peak-picking", "level": 1, "budget_calls": 16, "example_question": "Build the peak table for spectrum.csv following sop.md. Write output/peaks.json as a JSON list like [{\"position_cm1\": 1234.5, \"height\": 456.7}], sorted by position.", "answer_format": "output/peaks.json", "files": ["sop.md", "spectrum.csv"], "deliverable": "output/peaks.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "peak-picking-L2", "domain": "natural-science", "family": "peak-picking", "level": 2, "budget_calls": 20, "example_question": "Build the peak table for spectrum.csv following sop.md. Write output/peaks.json as a JSON list like [{\"position_nm\": 1234.5, \"height\": 456.7}], sorted by position.", "answer_format": "output/peaks.json", "files": ["sop.md", "spectrum.csv"], "deliverable": "output/peaks.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "dilution-plan-L1", "domain": "natural-science", "family": "dilution-plan", "level": 1, "budget_calls": 16, "example_question": "Write the pipetting plan for targets.csv using the stock in reagent.txt: output/plan.csv with columns tube,stock_uL,diluent_uL (volumes in microlitres).", "answer_format": "output/plan.csv", "files": ["reagent.txt", "targets.csv"], "deliverable": "output/plan.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "dilution-plan-L2", "domain": "natural-science", "family": "dilution-plan", "level": 2, "budget_calls": 20, "example_question": "Write the serial-dilution pipetting plan for series.csv and reagent.txt: output/plan.csv with columns tube,source,transfer_uL,diluent_uL, where source is 'stock' or the tube it is drawn from and volumes are in microlitres.", "answer_format": "output/plan.csv", "files": ["reagent.txt", "series.csv"], "deliverable": "output/plan.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "pk-fit-L1", "domain": "natural-science", "family": "pk-fit", "level": 1, "budget_calls": 16, "example_question": "Run the non-compartmental analysis in sap.md on plasma.csv (RT-2209) and write output/pk.json with keys k_el_per_h, half_life_h, auc_0_last, auc_0_inf (ng*h/mL), cmax (ng/mL) and tmax_h.", "answer_format": "output/pk.json", "files": ["plasma.csv", "sap.md"], "deliverable": "output/pk.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "pk-fit-L2", "domain": "natural-science", "family": "pk-fit", "level": 2, "budget_calls": 20, "example_question": "Run the non-compartmental analysis in sap.md on plasma.csv (candidate A) and write output/pk.json with keys k_el_per_h, half_life_h, auc_0_last, auc_0_inf (ng*h/mL), cmax (ng/mL) and tmax_h.", "answer_format": "output/pk.json", "files": ["dosing.txt", "plasma.csv", "sap.md"], "deliverable": "output/pk.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "linear-system-L1", "domain": "mathematics-or-formal-reasoning", "family": "linear-system", "level": 1, "budget_calls": 16, "example_question": "Solve the linear system in equations.txt for x1, x2, x3, x4. Write output/solution.json mapping each variable to its exact value as a string, e.g. {\"x1\": \"-7/3\"}.", "answer_format": "output/solution.json", "files": ["equations.txt"], "deliverable": "output/solution.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "linear-system-L2", "domain": "mathematics-or-formal-reasoning", "family": "linear-system", "level": 2, "budget_calls": 20, "example_question": "Solve the linear system in equations.txt for x1, x2, x3, x4, x5, x6 (read notes.txt first). Write output/solution.json mapping each variable to its exact value as a string, e.g. {\"x1\": \"-7/3\"}.", "answer_format": "output/solution.json", "files": ["equations.txt", "notes.txt"], "deliverable": "output/solution.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "recurrence-id-L1", "domain": "mathematics-or-formal-reasoning", "family": "recurrence-id", "level": 1, "budget_calls": 16, "example_question": "sequence.txt holds the first terms of an integer sequence that satisfies a linear recurrence a_n = c_1 a_{n-1} + ... + c_k a_{n-k} with constant integer coefficients. Find the one with the smallest order k and write output/answer.json as {\"coefficients\": [c_1, ..., c_k], \"next\": [the next 5 terms]}.", "answer_format": "output/answer.json", "files": ["sequence.txt"], "deliverable": "output/answer.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "recurrence-id-L2", "domain": "mathematics-or-formal-reasoning", "family": "recurrence-id", "level": 2, "budget_calls": 20, "example_question": "sequence.txt holds the first terms of an integer sequence that satisfies a recurrence a_n = c_1 a_{n-1} + ... + c_k a_{n-k} + d with constant integer coefficients and a constant integer d. Find the form with the smallest k (d may be 0) and write output/answer.json as {\"coefficients\": [c_1, ..., c_k], \"constant\": d, \"term_mod\": a_518046 mod 1000000007} (the term index starts at a_0; give the least non-negative residue).", "answer_format": "output/answer.json", "files": ["sequence.txt"], "deliverable": "output/answer.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "claim-check-L1", "domain": "mathematics-or-formal-reasoning", "family": "claim-check", "level": 1, "budget_calls": 16, "example_question": "Check each claim in claims.txt exactly (by exhaustive computation over its stated range). Write output/verdicts.json mapping each claim id to {\"holds\": true} or {\"holds\": false, \"counterexample\": n}, where n is the SMALLEST n in the claim's range for which it fails.", "answer_format": "output/verdicts.json", "files": ["claims.txt"], "deliverable": "output/verdicts.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "claim-check-L2", "domain": "mathematics-or-formal-reasoning", "family": "claim-check", "level": 2, "budget_calls": 20, "example_question": "Check each claim in claims.txt exactly (by exhaustive computation over its stated range). Write output/verdicts.json mapping each claim id to {\"holds\": true} or {\"holds\": false, \"counterexample\": n}, where n is the SMALLEST n in the claim's range for which it fails.", "answer_format": "output/verdicts.json", "files": ["claims.txt"], "deliverable": "output/verdicts.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "board-expectation-L1", "domain": "mathematics-or-formal-reasoning", "family": "board-expectation", "level": 1, "budget_calls": 16, "example_question": "A solo player plays the game in rules.txt. What is the exact expected number of turns until they reach home? Write output/answer.json as {\"expected_turns\": \"p/q\"} with a reduced fraction.", "answer_format": "output/answer.json", "files": ["rules.txt"], "deliverable": "output/answer.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "board-expectation-L2", "domain": "mathematics-or-formal-reasoning", "family": "board-expectation", "level": 2, "budget_calls": 20, "example_question": "A solo player plays the game in rules.txt. What is the exact expected number of turns until they reach home? Write output/answer.json as {\"expected_turns\": \"p/q\"} with a reduced fraction.", "answer_format": "output/answer.json", "files": ["rules.txt"], "deliverable": "output/answer.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "web-forensics-L1", "domain": "cybersecurity", "family": "web-forensics", "level": 1, "budget_calls": 16, "example_question": "access.log is an nginx combined log. One client is running a vulnerability scanner (it requests many different sensitive paths and almost all of them return 404). Write output/incident.json with keys attacker_ip, first_seen and last_seen (that client's first and last request, ISO 8601 UTC like 2026-03-01T14:05:09Z), request_count (all requests from that IP) and paths_200 (sorted list of the paths that returned 200 to it).", "answer_format": "output/incident.json", "files": ["access.log"], "deliverable": "output/incident.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "web-forensics-L2", "domain": "cybersecurity", "family": "web-forensics", "level": 2, "budget_calls": 20, "example_question": "access.log is a merged nginx combined log (lines are NOT in time order; timestamps carry the server's UTC offset). Exactly one client attempted SQL injection (UNION SELECT, tautologies like ' OR 1=1, stacked queries, SLEEP, comment terminators). Write output/incident.json with keys attacker_ip, first_seen and last_seen (that client's first and last request of any kind, ISO 8601 UTC like 2026-03-01T14:05:09Z), request_count (all requests from that IP), and paths_200: the sorted list of that client's injection request paths (exactly as logged, query string included) that returned 200.", "answer_format": "output/incident.json", "files": ["access.log"], "deliverable": "output/incident.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "decode-chain-L1", "domain": "cybersecurity", "family": "decode-chain", "level": 1, "budget_calls": 16, "example_question": "Decode every blob in artefacts.txt (notes.txt has the key) and crack every hash against wordlist.txt. Write output/decoded.json as {\"blobs\": {\"B1\": \"plaintext\", ...}, \"hashes\": {\"H1\": {\"algorithm\": \"md5\", \"password\": \"...\"}, ...}} (algorithm one of md5, sha1, sha256, sha512).", "answer_format": "output/decoded.json", "files": ["artefacts.txt", "notes.txt", "wordlist.txt"], "deliverable": "output/decoded.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "decode-chain-L2", "domain": "cybersecurity", "family": "decode-chain", "level": 2, "budget_calls": 20, "example_question": "Decode every blob in artefacts.txt (notes.txt has the key) and crack every hash against wordlist.txt. Write output/decoded.json as {\"blobs\": {\"B1\": \"plaintext\", ...}, \"hashes\": {\"H1\": {\"algorithm\": \"md5\", \"password\": \"...\"}, ...}} (algorithm one of md5, sha1, sha256, sha512).", "answer_format": "output/decoded.json", "files": ["artefacts.txt", "notes.txt", "wordlist.txt"], "deliverable": "output/decoded.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "sshd-audit-L1", "domain": "cybersecurity", "family": "sshd-audit", "level": 1, "budget_calls": 14, "example_question": "Audit sshd_config against baseline.md. Write output/findings.json as {\"failing\": [\"SSH-02\", ...]} listing the ids of every failing rule, sorted.", "answer_format": "output/findings.json", "files": ["baseline.md", "sshd_config"], "deliverable": "output/findings.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "sshd-audit-L2", "domain": "cybersecurity", "family": "sshd-audit", "level": 2, "budget_calls": 18, "example_question": "Audit sshd_config against baseline.md. Write output/findings.json as {\"failing\": [\"SSH-02\", ...]} listing the ids of every failing rule, sorted.", "answer_format": "output/findings.json", "files": ["baseline.md", "sshd_config"], "deliverable": "output/findings.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "jwt-inspect-L1", "domain": "cybersecurity", "family": "jwt-inspect", "level": 1, "budget_calls": 16, "example_question": "Inspect every JWT in tokens.txt using the rules in verifier.md. Write output/report.json mapping each token id to {\"valid\": true/false, \"reason\": \"<code>\", \"sub\": \"<sub claim>\"}.", "answer_format": "output/report.json", "files": ["tokens.txt", "verifier.md"], "deliverable": "output/report.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "jwt-inspect-L2", "domain": "cybersecurity", "family": "jwt-inspect", "level": 2, "budget_calls": 20, "example_question": "Inspect every JWT in tokens.txt using the rules in verifier.md. Write output/report.json mapping each token id to {\"valid\": true/false, \"reason\": \"<code>\", \"sub\": \"<sub claim>\"}.", "answer_format": "output/report.json", "files": ["tokens.txt", "verifier.md"], "deliverable": "output/report.json", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "srt-retime-L1", "domain": "media-content-production", "family": "srt-retime", "level": 1, "budget_calls": 14, "example_question": "subs.srt is 2656 ms late against the video: every subtitle must be shown 2656 ms earlier. Write the corrected file to output/out.srt (same cues and text, standard SRT timestamps HH:MM:SS,mmm).", "answer_format": "output/out.srt", "files": ["subs.srt"], "deliverable": "output/out.srt", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "srt-retime-L2", "domain": "media-content-production", "family": "srt-retime", "level": 2, "budget_calls": 20, "example_question": "Retime subs.srt for the new video cut using sync.txt and style.md, and write the deliverable subtitle file to output/out.srt.", "answer_format": "output/out.srt", "files": ["style.md", "subs.srt", "sync.txt"], "deliverable": "output/out.srt", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "image-audit-L1", "domain": "media-content-production", "family": "image-audit", "level": 1, "budget_calls": 16, "example_question": "Audit every image under assets/ against spec.md. Write output/report.csv with columns file,format,width,height,ok,reasons: file as listed (e.g. assets/hero.jpg), format as JPEG/PNG/GIF/WEBP, displayed width and height in px, ok as true/false, and reasons as the failing reason codes joined by ';' in spec order (empty when ok).", "answer_format": "output/report.csv", "files": ["assets/avatar.jpg", "assets/banner.jpg", "assets/card.png", "assets/gallery-1.png", "assets/hero.jpg", "assets/logo.jpg", "spec.md"], "deliverable": "output/report.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "image-audit-L2", "domain": "media-content-production", "family": "image-audit", "level": 2, "budget_calls": 20, "example_question": "Audit every image under assets/ against spec.md. Write output/report.csv with columns file,format,width,height,ok,reasons: file as listed (e.g. assets/hero.jpg), format as JPEG/PNG/GIF/WEBP, displayed width and height in px, ok as true/false, and reasons as the failing reason codes joined by ';' in spec order (empty when ok).", "answer_format": "output/report.csv", "files": ["assets/avatar.jpg", "assets/banner.png", "assets/card.jpg", "assets/gallery-1.jpg", "assets/hero.gif", "assets/logo.gif", "spec.md"], "deliverable": "output/report.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "audio-audit-L1", "domain": "media-content-production", "family": "audio-audit", "level": 1, "budget_calls": 16, "example_question": "Measure every WAV under audio/ as spec.md defines and write output/audio_report.csv with columns file,sample_rate,channels,duration_s,peak_dbfs (one row per file, file as listed, e.g. audio/intro.wav).", "answer_format": "output/audio_report.csv", "files": ["audio/intro.wav", "audio/outro.wav", "audio/sfx_door.wav", "audio/sting.wav", "audio/vo_take2.wav", "spec.md"], "deliverable": "output/audio_report.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "audio-audit-L2", "domain": "media-content-production", "family": "audio-audit", "level": 2, "budget_calls": 20, "example_question": "Measure every WAV under audio/ as spec.md defines and write output/audio_report.csv with columns file,sample_rate,channels,duration_s,peak_dbfs,clipped_samples,clipping (one row per file, file as listed, e.g. audio/intro.wav; clipping as true/false).", "answer_format": "output/audio_report.csv", "files": ["audio/intro.wav", "audio/outro.wav", "audio/sfx_door.wav", "audio/sting.wav", "audio/vo_take2.wav", "spec.md"], "deliverable": "output/audio_report.csv", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "markdown-html-L1", "domain": "media-content-production", "family": "markdown-html", "level": 1, "budget_calls": 16, "example_question": "Convert article.md to HTML following style.md exactly and write it to output/article.html.", "answer_format": "output/article.html", "files": ["article.md", "style.md"], "deliverable": "output/article.html", "style": "file", "new_in_v4": true, "in_training_list": true}
+{"task_id": "markdown-html-L2", "domain": "media-content-production", "family": "markdown-html", "level": 2, "budget_calls": 20, "example_question": "Convert article.md to HTML following style.md exactly and write it to output/article.html.", "answer_format": "output/article.html", "files": ["article.md", "style.md"], "deliverable": "output/article.html", "style": "file", "new_in_v4": true, "in_training_list": true}