brilliantrough/agent-skills

exp-probe

Run one-off research spot experiments with minimal ceremony.

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원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Exp Probe: ask once if needed → run → record → one line

A probe exists to answer one question cheaply. Everything about it is minimal except honesty.

  • Define the single question first ("does config X fit in memory", "is this NaN reproducible", "what is the missing anchor value"). If you cannot name the question, this is not a probe.
  • Shrink, don't distort: reduce sample counts and steps, never the semantics being measured (sequence length, batch semantics, dtype). State exactly what was shrunk when reporting.
  • Reproduce the real entry point: probes run through the same launcher/flags as the real run (e.g., a preflight mode), not a rewritten ad-hoc path — a probe that bypasses the real path proves nothing about it. Probe code lives in the project's scratch/experiment area, isolated per probe, and follows the same rule as all research code: no defensive programming — minimum code, real errors exit as-is; environment failures (GPU contention, disk full) are diagnosed as environment, not patched around.
  • One question to the user at most, and only if the question itself is ambiguous. No plan docs, no grilling rounds, no sub-agents.
  • Record where the campaign can find it: scratch area per project rules, with config, observation, and exit status. If the probe's answer prunes campaign cells, the claim and its evidence belong in the campaign's pruning ledger — say which cells it affects.
  • Report in one line: question, observed answer, cost, and what it unblocks or rules out. If the answer is "unknown/inconclusive", say that and propose the next smallest probe — do not upgrade it silently into a batch.
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brilliantrough
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code-review

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to \"review since X\".

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1
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3
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9월 20일
brilliantrough
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domain-modeling

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.

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1
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3
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9월 20일
brilliantrough
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grill-with-docs

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

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1
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3
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9월 20일
brilliantrough
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migrate-mem

Establish useful memory for a project that already has development history, or improve an incomplete memory setup. Survey the project and its existing evidence, then initialize or enrich human-readable StrictDoc docs/ with current norms and historical context. Use Magic Context and other available memory alongside it where useful. No previous workflow, legacy folder convention, or pre-existing StrictDoc skeleton is assumed.

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1
GitHub Stars
3
업데이트
9월 20일