update dataset card

README.md

@@ -0,0 +1,92 @@
+---
+license: mit
+language:
+- en
+task_categories:
+- text-classification
+pretty_name: evalroute-tasks
+size_categories:
+- n<1K
+tags:
+- evalroute
+- task-routing
+- coding-agents
+---
+
+evalroute-tasks
+===============
+
+A small human-labeled corpus for training and evaluating `evalroute`'s
+task→lane router. Each row is one real coding/research/writing task with the
+lane a human asserts it belongs to. Tier 1 (task → lane) is the only required
+label today; the schema leaves room for tier 2 (task → arm outcome) and tier 3
+(task → done artifact) so contributors can backfill later without a format
+break.
+
+Status: zero to one. One contributor, 54 rows, four of nine lanes. Per lane:
+routine-coding 30, dl-ml-research-engineering 13, alignment-reasoning 10, prose 1;
+hard-agentic-coding, long-doc-reading, web-research, math-first-principles and
+orchestration have none yet. 24 rows are real tasks pinned in one dispatcher's
+ledger (mostly coding briefs), 30 are hand-written tier-a taskset rows. n is small
+and the mix reflects one person's work — that is the point of publishing it:
+your work shapes your router, and the shared encoder is only as broad as this
+file. The trained encoder is `keppy/evalroute-lane-encoder`; the outcomes
+flywheel (lane/arm/verdict, no text) is `keppy/evalroute-flywheel`.
+
+Tiers
+-----
+
+| Tier | Question            | Keys                                     | Required |
+|------|---------------------|------------------------------------------|----------|
+| 1    | which lane?         | id, text, label, source, contributor, week | yes    |
+| 2    | which arm, and did it work? | arm, verdict, method, n          | optional (all-or-none) |
+| 3    | how was done judged? | checker / rubric / reference (at most one) | optional |
+
+Row example
+-----------
+
+```json
+{"id": "keppy:a3f9c1", "text": "add a CLI verb that reads the ledger and prints per-lane counts",
+ "label": "routine-coding", "source": "ledger-pinned", "contributor": "keppy", "week": "2026-W40",
+ "arm": "z-ai/glm-5.3-flash@medium", "verdict": "pass", "method": "measured", "n": 10,
+ "checker": null, "rubric": null, "reference": null}
+```
+
+The publish gate (three steps, all must pass)
+---------------------------------------------
+
+1. Mechanical validation: `python scripts/validate.py tasks/*.jsonl` checks
+   id/text/lane/source/contributor/week format, tier-2 and tier-3 coherence,
+   and a secret/PII/hostname regex gate over `text` and tier-3 strings.
+2. Denylist: if `private_terms.txt` exists in the repo root (git-ignored) or
+   you pass `--private-terms <file>`, any case-insensitive whole-word hit fails
+   the row. Keep employer/project terms you must not publish in that file.
+3. Human review: run `python scripts/review.py tasks/<you>.jsonl`, read every
+   numbered row, compute the batch sha, add
+   `reviewed: <sha>  <date>  <contributor>` to `REVIEWED.md`, then open a PR.
+   `scripts/upload.py` refuses to touch Hugging Face unless `REVIEWED.md`
+   contains a line for every file's sha.
+
+How to contribute
+-----------------
+
+1. Fork/branch, add your own file `tasks/<your-handle>.jsonl` (one JSON row per
+   line; the file stem and row-id prefix must be your handle).
+2. Run `python scripts/validate.py tasks/<your-handle>.jsonl` — it must exit 0.
+3. Run `python scripts/review.py tasks/<your-handle>.jsonl`, actually read the
+   rows, and add the printed `reviewed:` line to `REVIEWED.md`.
+4. Open a PR. A reviewer re-runs validate and diff-checks your rows.
+
+What is not here
+----------------
+
+No paraphrases: train F showed paraphrases that outnumber real rows pull the
+classifier toward the paraphrase dialect. No ledger exports without review —
+a row lands here only after a human decided the text is safe to publish. No
+personal or employer details: names, internal hostnames, credentials, and
+project-denialist terms are caught by the gate, but judgment is still yours.
+
+License
+-------
+
+MIT, see LICENSE (copyright 2026 keppy).