keppy/evalroute-flywheel

evalroute flywheel

Honest size: three lanes are measured (n=10 each; arms tied at p=1.0) and six are priors from public benchmarks — not our runs. The pipe is real, the table is small, your outcomes grow it.

Configs: measured — Tier-A harness artifacts (runs.jsonl, report.csv, tasks.jsonl, models manifests); written only by harness runs, never accepts contributed rows · routes — the routes.yaml that evalroute sync pins (MANIFEST.json says what produced it) · contributed — redacted outcome rows from opted-in installs under contributed/<contributor>/.

What a contributed row carries — only this, whitelist-redacted

key	what it is
kind	always outcome
route_lane, route_model, route_effort	the routed arm
actual_model, actual_effort, arm_attribution	the arm you actually ran (only when you confirmed it)
method, confidence	how the route was classified
rated	pass / fail / skip (rating corrections applied)
facets	counts only, e.g. {"long-doc": 1}
week	ISO year-week (2026-W40) — no timestamps
task_hash	HMAC-SHA256 of the task text under a per-install salt
corrected, schema	correction flag; schema version

Never leaves: task text, notes, paths, hostnames, session keys, the salt, the token.

This dataset answers "which arm wins on which lane" and the text was never the signal there, so stripping it costs nothing. The classifier's input is the text, and that needs a different object: https://huggingface.co/datasets/keppy/evalroute-tasks — real tasks with human-asserted lanes, published on purpose after a review, no paraphrases. Outcomes here, text there; the lane ids are the shared vocabulary between them.

uv tool install evalroute                    # or: pip install evalroute
evalroute route --json "<one-line task>"     # -> lane, model, effort, route_id
# ... run the task on that arm, your own way ...
evalroute rate pass --route-id <id> --model <model> --effort <effort> --note "why" --json
evalroute report --json                      # what the ledger says so far
evalroute contribute --dry-run               # the exact rows that would go; grep, then drop the flag

Pooled rows are observational: they can contest a priors lane, never overwrite a measured one.

• code + contract: https://github.com/keppy/evalroute (see its AGENTS.md)
• Hermes plugin: https://github.com/keppy/hermes-plugin-evalroute
• task corpus (text, reviewed): https://github.com/keppy/evalroute-tasks
• lane encoder (opt-in): https://huggingface.co/keppy/evalroute-lane-encoder