Align MiMo folder and README with other v1 datasets

Restore the compact stats-first README and the standard README, patcher, tasks and archive layout. Embed the image-digest mapping in patch.py. Audit evidence remains accessible at the linked original publication revision. The self-contained patcher reproduces both task and archive Parquets byte-for-byte; 2,509 retained tasks and 1,189 archives are unchanged.

mimo_v1/README.md

@@ -1,36 +1,51 @@
-# mimo_v1
+# [MiMo-V2.6-RL Code](https://huggingface.co/datasets/XiaomiMiMo/MiMo-V2.6-RL-oss/tree/639865fd3374018d6cb29b9fb82dd531406fcf5f)
 
-## Original datasource
+## Dataset stats
 
-- MiMo-V2.6-RL-oss (code subset) — Xiaomi MiMo-V2.6 RL environments — https://arxiv.org/abs/2610.11959
+- **Original tasks:** 3,698 (2,698 Code, 1,000 Cyber)
+- **Kept:** 2,509
+- **Changed:** 2,509 (converted to Harbor)
+- **Archived:** 1,189
+- **Images:** 2,509 retained task environments, each using its own pinned upstream image. No shared-image condensation; cached Apptainer images are not included in this release.
 
-## Domains
+## Dataset characteristics
 
-Software Engineering, Debugging
+Implement a feature or fix a bug in a real open-source repository, graded by the upstream hidden tests.
 
-- **Software Engineering:** Every sampled task drops the agent into a real open-source repository at /testbed (thundernetes/Go, Sentry/JS, Home Assistant/Python, Lerna/TS, accessibility-insights-web/TS, redux-saga-firebase/JS, tablewriter/Go, Pygments/Python, mypy/Python, tough-cookie/JS) and asks for a code change: new API methods (ClearRows/ClearFooter, CookieJar serialize/deserialize/clone), new CLI options (lerna exec --env-file), extended request/response handling, or init-container behavior. Reward is 1.0 only if a hidden test patch (applied by tests/setup.sh) passes via the published test command, so the deliverable is working application code in Go, Python, JavaScript, and TypeScript.
-- **Debugging:** Roughly half of the sampled instructions are issue-style bug reports rather than feature specs: mypy not flagging `raise SomeException` without instantiation, Pygments highlighting PEP 657 caret markers as operators, Brother printer zeroconf flow reporting the wrong abort reason, Sentry's environment dropdown leaking other projects' environments, TabInfo rendering an empty div. The agent must localize the faulty code from a symptom description and repair it so fail-to-pass tests (and retained pass-to-pass tests) succeed.
+<details><summary>Domains</summary>
 
-## Agent capabilities
+**Software Engineering:** repository APIs, command-line options, request handling and application behavior in Python, Go, JavaScript and TypeScript. **Debugging:** locate faulty code from an issue description and repair the behavior checked by regression tests.
 
-Exploration, Specification Adherence, Constraint Satisfaction, Error Recovery
+</details>
+<details><summary>Capabilities</summary>
 
-- **Exploration:** Intended practice: instructions name symptoms or desired public API but not file locations ('the specific component boundaries, state plumbing, and validation location are up to the implementation'), and the hidden tests reference internal names (e.g. EnvironmentSelectorItem, PublicIpV4Address, GameServerConnectionInfo, MemoryCookieStore). The agent has to navigate an unfamiliar multi-thousand-file repo, find the relevant module and existing test conventions, and figure out how to run the project's test suite before changing anything. No trajectories were supplied, so this is inferred from task design, not observed behavior.
-- **Specification Adherence:** Intended practice: several instructions are long, precise contracts whose details are checked verbatim by the hidden tests — exact error strings ('Environment file not found: &lt;path&gt;', 'Invalid environment assignment "&lt;entry&gt;"; expected KEY=VALUE'), a five-layer env merge precedence, case-insensitive Content-Type handling with a '+json' subtype rule, serialized field names like `version: "tough-cookie@&lt;ver&gt;"` and `storeType`, ISO-8601 dates, and preserved cookie ordering. Partial or drifted implementations fail the binary reward, so the agent must recheck the full contract before finishing. Inferred from instructions and test patches; no trajectories observed.
-- **Constraint Satisfaction:** Intended practice: tasks pair new behavior with hard backward-compatibility requirements, and verifiers enforce both. The redux-saga-firebase task must add POST/JSON handling while keeping the legacy GET effect shape; the Lerna task must add env overlays while existing invocations keep working and LERNA_* variables are always forced; the Sentry verifier runs the pre-existing test suite (base) and the new tests (new) and requires both to pass; the tough-cookie and Lerna commands run old suites alongside the new spec. The agent must reconcile 'do not break existing tests' with 'satisfy the new contract'. Inferred from verifier scripts, not from observed trajectories.
-- **Error Recovery:** Intended practice only: the environment exposes the project's test runners (go test, pytest, jest, vows) and the natural loop is to implement, run tests, read failures, and fix. Nothing in the supplied evidence shows this happening, since no trajectories were provided, and the hidden test patch is not visible to the agent during the episode, so the agent can only iterate against its own or existing tests.
+**Exploration:** navigate unfamiliar repositories and find the relevant implementation. **Specification Adherence:** satisfy precise API, output and error-handling requirements. **Constraint Satisfaction:** implement new behavior while preserving existing behavior. **Error Recovery:** use test feedback to guide repairs. These are intended capabilities inferred from task content, not measured agent behavior. Labels follow [CLI-Universe](https://arxiv.org/abs/2606.22883v1).
 
-## Expected benchmark transfer
+</details>
 
-- **SWE-bench Verified random-100**: This is the same task format: a GitHub-issue-style statement, a repository checkout at /testbed, a hidden fail-to-pass test patch applied at verification time, and a binary pass/fail reward from the project's test runner, executed through a Terminus-2-compatible container (the Dockerfile installs tmux for that harness). The Python tasks in the sample (mypy, Pygments, Home Assistant) use the same pytest-driven verification SWE-bench relies on, so practicing issue localization, repo navigation, and patch writing here should directly raise the solve rate.
-- **DeepSWE 1.1 (deep-swe-litecontainer@1.1)**: DeepSWE is a lightweight-container SWE-style repair/feature benchmark with executable verification; the sampled tasks exercise exactly that loop (read issue, find code, implement, run tests) across Python, Go, JavaScript, and TypeScript repos, so the trained behaviors should carry over even though the benchmark is out of distribution for the suite.
-- **Terminal-Bench 2.0**: Tasks are run as Harbor/Terminus-2 terminal-agent episodes in a container: the agent must use the shell to locate code, install or invoke toolchains (go, yarn, npx jest, pytest, vows), edit files, and verify with tests. That is the core skill Terminal-Bench 2.0 measures, so modest transfer is expected on its software-engineering-flavored tasks, with less effect on its sysadmin and data tasks.
-- **OpenThoughts-TBLite 2.0**: TBLite is calibrated against Terminal-Bench 2 and uses the same Terminus-2 harness and verifier-success scoring; the same reasoning applies: long-horizon container tool use, repo editing, and test execution learned from these tasks should lift the coding-oriented portion of the panel.
+Intended benchmark transfer: **SWE-bench Verified, Terminal-Bench 2.0 and OpenThoughts-TBLite 2.0**, through issue-driven repository work, terminal tools and executable verification.
 
-## Files
+## Per-stage breakdown
 
-- `tasks.parquet`: kept tasks.
-- `archive.parquet`: excluded tasks with validation reasons.
+- **Build and setup: 2,509 accepted, 1,103 archived.** Converted the retained Code rows to Harbor tasks with pinned images, terminal support and verifier setup. Archived: 1,000 Cyber tasks requiring separate operating-system users, 96 removed upstream images, 4 images with incomplete package installations and 3 images containing solution or hidden-test residue.
+- **No-op baseline (reward 0): 2,509 accepted, 86 archived.** Raised memory limits for 94 tasks to 8 or 16 GiB after profiling. Archived: 52 tasks incompatible with the runtime, 22 with broken environments or impractical build requirements, 10 with repository defects and 2 without reliable test-execution evidence. Reviewed expected failures and execution-recording gaps count as accepted zeros; the original reports are preserved in the linked evidence below.
+- **Reference solution (reward 1): not applicable.** The upstream rows contain no reference solutions.
+- **Rule-based checks: 2,509 accepted, 0 archived.** Automatic instruction-path resolution and the timeout/anti-cheat suffix were enabled. Advisory warnings and excluded checks are recorded in the validation evidence.
 
-Generated with claude-fable-5-1; domain and capability labels follow CLI-Universe.
-Taxonomy source: https://arxiv.org/abs/2606.22883v1
+Includes the full validation run and reruns of repaired tasks. Task `002797` also showed a Jest worker serialization crash, and `000133` showed connection-refused errors in other tests; each has independent assertions reproducing the requested bug. Their acceptance establishes a valid no-op zero, not complete verifier health.
+
+## Runtime and validation time
+
+- **Versions:** Apptainer **1.5.4** on the main Helma run, Python **3.12.14**, Harbor **0.8.1**.
+- **Implementation:** [Marin Harbor `7faf878c14b6`](https://github.com/marin-community/harbor/tree/7faf878c14b6d72737579ec936ebf5f74ba3194d) with [our runtime patches](https://github.com/MLI-lab/OT-next-data/tree/main/harbor_patches).
+- **Resources:** main Helma run: **48 CPU cores, 128 GiB RAM**, up to 8 concurrent tasks per job. Final CLAIX retry: **32 CPU cores, 128 GiB RAM**, up to 6 concurrent tasks.
+
+| Check | Median per task | Tasks measured |
+| --- | ---: | ---: |
+| Build and setup | **22.5 s** | 2,509 |
+| No-op baseline | **28.1 s** | 2,509 |
+| Rule-based checks | **0.1 s** | 2,509 |
+
+Medians use the selected compatible results for the retained tasks, not total runtime including retries or queue time.
+
+Detailed [validation records](https://huggingface.co/datasets/FWeindel/validated-tasks/blob/49b508461095e98fa721b0f1b0b7939a594e8653/mimo_v1/validation.json), [no-op reviews](https://huggingface.co/datasets/FWeindel/validated-tasks/blob/49b508461095e98fa721b0f1b0b7939a594e8653/mimo_v1/noop-review.json) and [original logs](https://huggingface.co/datasets/FWeindel/validated-tasks/blob/49b508461095e98fa721b0f1b0b7939a594e8653/mimo_v1/noop-review-evidence.tar.gz) remain available at the original publication revision.

mimo_v1/annotation.json

@@ -1,75 +0,0 @@
-{
-  "annotation": {
-    "dataset_name": "mimo_v1",
-    "original_datasources": [
-      {
-        "name": "MiMo-V2.6-RL-oss (code subset) \u2014 Xiaomi MiMo-V2.6 RL environments",
-        "url": "https://arxiv.org/abs/2610.11959"
-      }
-    ],
-    "domains": [
-      {
-        "label": "Software Engineering",
-        "reason": "Every sampled task drops the agent into a real open-source repository at /testbed (thundernetes/Go, Sentry/JS, Home Assistant/Python, Lerna/TS, accessibility-insights-web/TS, redux-saga-firebase/JS, tablewriter/Go, Pygments/Python, mypy/Python, tough-cookie/JS) and asks for a code change: new API methods (ClearRows/ClearFooter, CookieJar serialize/deserialize/clone), new CLI options (lerna exec --env-file), extended request/response handling, or init-container behavior. Reward is 1.0 only if a hidden test patch (applied by tests/setup.sh) passes via the published test command, so the deliverable is working application code in Go, Python, JavaScript, and TypeScript."
-      },
-      {
-        "label": "Debugging",
-        "reason": "Roughly half of the sampled instructions are issue-style bug reports rather than feature specs: mypy not flagging `raise SomeException` without instantiation, Pygments highlighting PEP 657 caret markers as operators, Brother printer zeroconf flow reporting the wrong abort reason, Sentry's environment dropdown leaking other projects' environments, TabInfo rendering an empty div. The agent must localize the faulty code from a symptom description and repair it so fail-to-pass tests (and retained pass-to-pass tests) succeed."
-      }
-    ],
-    "capabilities": [
-      {
-        "label": "Exploration",
-        "reason": "Intended practice: instructions name symptoms or desired public API but not file locations ('the specific component boundaries, state plumbing, and validation location are up to the implementation'), and the hidden tests reference internal names (e.g. EnvironmentSelectorItem, PublicIpV4Address, GameServerConnectionInfo, MemoryCookieStore). The agent has to navigate an unfamiliar multi-thousand-file repo, find the relevant module and existing test conventions, and figure out how to run the project's test suite before changing anything. No trajectories were supplied, so this is inferred from task design, not observed behavior."
-      },
-      {
-        "label": "Specification Adherence",
-        "reason": "Intended practice: several instructions are long, precise contracts whose details are checked verbatim by the hidden tests \u2014 exact error strings ('Environment file not found: <path>', 'Invalid environment assignment \"<entry>\"; expected KEY=VALUE'), a five-layer env merge precedence, case-insensitive Content-Type handling with a '+json' subtype rule, serialized field names like `version: \"tough-cookie@<ver>\"` and `storeType`, ISO-8601 dates, and preserved cookie ordering. Partial or drifted implementations fail the binary reward, so the agent must recheck the full contract before finishing. Inferred from instructions and test patches; no trajectories observed."
-      },
-      {
-        "label": "Constraint Satisfaction",
-        "reason": "Intended practice: tasks pair new behavior with hard backward-compatibility requirements, and verifiers enforce both. The redux-saga-firebase task must add POST/JSON handling while keeping the legacy GET effect shape; the Lerna task must add env overlays while existing invocations keep working and LERNA_* variables are always forced; the Sentry verifier runs the pre-existing test suite (base) and the new tests (new) and requires both to pass; the tough-cookie and Lerna commands run old suites alongside the new spec. The agent must reconcile 'do not break existing tests' with 'satisfy the new contract'. Inferred from verifier scripts, not from observed trajectories."
-      },
-      {
-        "label": "Error Recovery",
-        "reason": "Intended practice only: the environment exposes the project's test runners (go test, pytest, jest, vows) and the natural loop is to implement, run tests, read failures, and fix. Nothing in the supplied evidence shows this happening, since no trajectories were provided, and the hidden test patch is not visible to the agent during the episode, so the agent can only iterate against its own or existing tests."
-      }
-    ],
-    "expected_benchmark_transfer": [
-      {
-        "benchmark": "SWE-bench Verified random-100",
-        "reason": "This is the same task format: a GitHub-issue-style statement, a repository checkout at /testbed, a hidden fail-to-pass test patch applied at verification time, and a binary pass/fail reward from the project's test runner, executed through a Terminus-2-compatible container (the Dockerfile installs tmux for that harness). The Python tasks in the sample (mypy, Pygments, Home Assistant) use the same pytest-driven verification SWE-bench relies on, so practicing issue localization, repo navigation, and patch writing here should directly raise the solve rate."
-      },
-      {
-        "benchmark": "DeepSWE 1.1 (deep-swe-litecontainer@1.1)",
-        "reason": "DeepSWE is a lightweight-container SWE-style repair/feature benchmark with executable verification; the sampled tasks exercise exactly that loop (read issue, find code, implement, run tests) across Python, Go, JavaScript, and TypeScript repos, so the trained behaviors should carry over even though the benchmark is out of distribution for the suite."
-      },
-      {
-        "benchmark": "Terminal-Bench 2.0",
-        "reason": "Tasks are run as Harbor/Terminus-2 terminal-agent episodes in a container: the agent must use the shell to locate code, install or invoke toolchains (go, yarn, npx jest, pytest, vows), edit files, and verify with tests. That is the core skill Terminal-Bench 2.0 measures, so modest transfer is expected on its software-engineering-flavored tasks, with less effect on its sysadmin and data tasks."
-      },
-      {
-        "benchmark": "OpenThoughts-TBLite 2.0",
-        "reason": "TBLite is calibrated against Terminal-Bench 2 and uses the same Terminus-2 harness and verifier-success scoring; the same reasoning applies: long-horizon container tool use, repo editing, and test execution learned from these tasks should lift the coding-oriented portion of the panel."
-      }
-    ],
-    "no_transfer_reason": null,
-    "model": "claude-fable-5-1"
-  },
-  "provenance": {
-    "source_annotation": "/hnvme/workspace/y500bb12-optiagent/mimo-annotation-20261018/mimo_v1-annotation.json",
-    "sampled_task_ids": [
-      "format-code-task-000208",
-      "format-code-task-001270",
-      "format-code-task-001502",
-      "format-code-task-001773",
-      "format-code-task-001909",
-      "format-code-task-002008",
-      "format-code-task-002100",
-      "format-code-task-002383",
-      "format-code-task-002428",
-      "format-code-task-002560"
-    ],
-    "sample_retained_in_final_release": true
-  }
-}

mimo_v1/noop-review-evidence.tar.gz

@@ -1,3 +0,0 @@
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-oid sha256:5608167a24311f60b4bf45ef21fc6ef7e5a5145f5c21de10eeac73cbcef6aba6
-size 3568400

mimo_v1/noop-review.json

@@ -1,288 +0,0 @@
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mimo_v1/validation.json

@@ -1,3 +0,0 @@
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