ShiftDesk v4: training list capped at 50 tasks (32 new file-deliverable + 18 v3)

README.md

@@ -17,8 +17,9 @@ natural science, math and formal reasoning, cybersecurity, and media. Each asks
 (`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.
+The training list (`in_training_list` in `tasks.jsonl`) has 50 tasks, the arena's maximum: the 32 new ones (64%)
+interleaved with 18 v3 tasks from software, industrial, office and finance (36%), 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.

tasks.jsonl

@@ -7,19 +7,19 @@
 {"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-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": false}
 {"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-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": false}
 {"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-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": false}
 {"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}