--- type: howto title: Running autoresearch skill evals (setup, efficiency, quality) summary: How to set up and run an /autoresearch loop over Claude Code skill/hook wording against a model-tier eval grid — which run mode is valid, how to keep iterations fast, and how to keep results trustworthy. tags: - type/howto - domain/llm-evaluation - tool/claude-code - tool/autoresearch - project/cc-os scope: global last_updated: 2026-07-04 date: 2026-07-04 related: - os-adr-eval-b-grid-results-and-observations - cc-os-plugin-skill-naming-convention source: cc-os --- # Running autoresearch skill evals ## Opening Reach for this before designing or running any `/autoresearch` loop that optimizes Claude Code skill/hook wording against an eval grid (the os-adr Eval A / Eval B pattern, or any successor). It encodes what two full grid campaigns (2026-07-03 baseline, 2026-07-04 confirmation) taught about where the time and the false conclusions actually come from. The loop discipline assumed throughout: **only wording moves** — checker, fixtures, scenarios, and judge rubric are frozen for the duration of a loop. ## Prerequisites - [ ] A deterministic checker with per-axis output (e.g. axis a = triggered, axis b = correct outcome) — axis-level results locate WHICH wording surface to iterate. - [ ] A committed baseline grid with per-cell results, written to a durable note (not just /tmp TSVs). - [ ] Plugin caches verified fresh: run `cc-os/bin/refresh-plugins` — installs COPY plugin files into `~/.claude/plugins/cache/`, so SKILL.md/hook edits do NOT reach headless sessions until refreshed. - [ ] Environment frozen: no plugin renames, command-name changes, or hook rewires mid-loop — registered command names are part of what the model sees, so changing them mid-loop is a confound (see [[cc-os-plugin-skill-naming-convention]]). ## Steps ### Step 1: Pick the valid run mode for what you're measuring - **Prompted skill-execution evals (Eval A shape):** in-session Agent-tool subagents with pinned `model:` are valid and much cheaper than headless runs. - **Unprompted-behavior evals (Eval B shape):** headless-only — fresh `claude -p` per rep with cwd = sandbox so the real SessionStart hook fires. In-session subagents inherit the parent session and never get a fresh hook; they are invalid here. Do not conflate the two shapes. ### Step 2: Refresh caches after EVERY wording edit Each loop iteration edits SKILL.md / hook-note wording in the plugin source. Run `bin/refresh-plugins` before the grid run of every iteration, or the grid silently measures the previous iteration's wording. This is the single most likely way a loop produces garbage. ### Step 3: Use a reduced inner-loop grid; save the full grid for confirmation Iterate only on the target cells (the failing scenarios) plus one passing control cell (to catch regressions). Run the full grid only to confirm a winning candidate before locking it in. Cells that aren't moving are pure cost inside the loop. ### Step 4: Parallelize cells; drive scripts directly Each headless `claude -p` cell is fully independent — run them concurrently (background the per-cell `bin/run` invocations). Sandbox setup is a sub-second fixture copy; the live model session is the irreducible unit (~30s–5min per cell). A sequential 16-cell grid takes ~25–30 min; parallel, it's bounded by the slowest cell (~5 min). Drive the grid script directly from the session with background Bash — do NOT wrap it in a babysitting subagent (agents self-pause, need resuming, and re-runs collide with existing sandboxes: "refusing to overwrite"). ### Step 5: Use enough reps to beat the noise 1 rep/cell is demonstrably noisy: across the two os-adr campaigns, cells flipped between attempts (haiku W2 axis-a, sonnet W1 overall). Inside the loop use ~3 reps on target cells and accept a wording change only if it moves the majority of reps. Re-run the full grid with more reps once wording is stable, to measure variance explicitly. ### Step 6: Read failures at the axis level before writing new wording Different axes point at different wording surfaces. Example from the os-adr baseline: sonnet W3 fails axis b only (it consults the ADR system, then doesn't propose recording — iterate the create-skill's "when to record" guidance), while R1 fails axis a (never looks — iterate trigger salience in the hook note / find-skill description). One "failure" label, two different fixes. ## Verification - Baseline reproduces before you start: re-run the grid once post-any-environment-change; expect ≥90% cell agreement with the recorded baseline before trusting deltas. - After a claimed improvement: full grid + the degradation checks pass in the expected pattern. - Verify results from the primary TSV, not from an orchestrating agent's prose report — an agent report has contradicted the TSV on a cell before; the TSV is the truth. ## Gotchas - **Stale plugin cache** — symptoms: wording edits have zero effect across iterations, or hooks silently absent from transcripts. Recover: `bin/refresh-plugins`, re-run the iteration. - **Degradation-check cells (e.g. R4-nograph) are only meaningful paired with a PASS on their non-degraded twin at the same tier** — and at 1 rep they can pass "unexpectedly" (sonnet found the right ADR without the graph on 2026-07-04), which weakens the layer-value evidence rather than proving anything. Don't cite degradation cells as proof at 1 rep. - **Held-out scenarios stay held out** — never run scenario Task blocks informally/by hand; that contaminates the measurement. - **Broken cells look like model failures** — a missing `transcript.jsonl` scores FAIL on both axes. Check reasons strings for harness errors before counting a cell as a behavioral result. - **Model-tier gaps can be total** — haiku 0/8 on Eval B means wording iteration may not reach the lower tier at all; keep one lower-tier canary cell (haiku W2, the one axis-a flicker) in the loop to detect whether wording changes reach it. ## Related - [[os-adr-eval-b-grid-results-and-observations]] — the concrete baseline numbers and prompting-issue hypothesis any os-adr follow-up loop must compare against. - [[cc-os-plugin-skill-naming-convention]] — naming/registration mechanics; changing registered command names mid-loop is a confound.