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prime-radiant-inc/superpowers-autoresearch
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README.md

superpowers-autoresearch

Machinery for running autoresearch loops against superpowers skill behavior: hypothesis logs, micro-test harnesses, transcript mining, and report generators. Born from the 2026-06-10/11 SDD cost campaign (46 runs) and build-loop autoresearch (25 experiments).

The loop

  1. Hypothesis log first. Every experiment pre-registers a prediction in a dated log under logs/. Negative results get equal billing. Verdicts cite evidence. Durable results also copy to superpowers-evals docs/experiments/.
  2. Method tiers, cheapest first:
    • MINE — answer from existing run artifacts (free). Scripts in mining/.
    • MICRO — one API call per sample, guidance variant in realistic context, 5+ reps, ALWAYS a no-guidance control (~$0.15–0.50/sample). Harnesses in harnesses/.
    • FULL — quorum eval runs via superpowers-evals (~$7–15 each). Only when cheaper tiers can't answer.
  3. Quality gates guard config changes (planted-defect scenario et al.). Pass/fail alone is insufficient — read the gauntlet reasoning; runs pass while components fail.

Non-negotiable methodology (each rule bought with a real mistake)

  • Manually inspect every automated score match. Three scoring bugs in one campaign: a grep counting template echoes as findings, a harness that never inlined the diff it claimed to test, a regex blind across newlines.
  • No-guidance control in every micro battery. It exposed both a backfire (prohibition worse than nothing) and a working prohibition.
  • Zero-variance across reps is the signature of guidance that landed.
  • Single-run deltas under ~20% are noise on full eval runs.
  • Fixture realism bounds everything: hand-written fixture plans executed at ~2× the cost of real skill output. Generate fixtures with the system under test.
  • If the baseline won't fail, stop — inconclusive-by-zero ≠ pass; don't author guidance for failures you can't elicit.

Layout

  • harnesses/ — micro-test runners (self-contained Python, stdlib only; parameterized via env: MODEL, SPEC_FILE, OUT_DIR, VARIANTS). Caching per (variant, rep): reruns fill gaps.
  • mining/ — transcript/economics miners for quorum run dirs.
  • fixtures/ — design specs used by plan-generation micros.
  • logs/ — dated hypothesis logs + run mappings (the working records).
  • reports/ — generated HTML narratives/dashboards + generators.
  • campaigns/<name>/ — per-campaign battery: prompts, runner, researcher instructions, results.

Requirements

ANTHROPIC_API_KEY in env for micros. FULL runs go through a superpowers-evals checkout (uv run quorum run … from its evals dir — never cd away mid-command; SUPERPOWERS_ROOT points at the skill-config clone under test, which must NOT be edited while a run reads it).