code-reviewer
Non-interactive bmad-code-review adapter for conduct. Accepts a single story diff, drives adversarial bug-hunt in report-only mode, normalizes surviving findings to the canonical schema with stakes_class populated, and returns the finding stream to the Conductor. Invoked by the Conductor — do not invoke directly.
- License 许可
- Apache-2.0
- 最近更新
- 2026-11-09
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01 前言 Front Matter
- name
- spec-decide-tradeoffs
- description
- Use when a design choice has multiple valid options — produce a dimension-by-dimension trade-off table (fidelity, accuracy, scale, maintainability), justify one recommendation against long-term failure modes, and record it in the spec. Works with structured and design-doc layouts.
02 资源文件 4
- 参考文档agents/openai.yaml43 B
- 参考文档evals/eval-no-review-output-produced.md779 B
- 参考文档evals/eval-stub-invocation-response.md550 B
- 参考文档workflow.md19.5 KB
03 SKILL.md 正文
Decide an Architecture Choice via a Trade-off Table
When a clarification or design question has several defensible answers and the user asks "which is the better long-term solution / most fidelity / most value," do not just pick — show the reasoning as a scored comparison, then commit the decision to the artifact. This recurs whenever a spec leaves a storage model, aggregation strategy, scoring formula, or fetch cadence open.
- Enumerate the real options (2–4). State each as a concrete mechanism, not a label — e.g. "daily pre-aggregate, discard raw" vs "store raw alerts, aggregate at read time" vs "raw event log + materialized summary." Include any option the user already leans toward so it gets judged on equal footing.
- Pick the dimensions that actually matter for THIS choice. Default long-term lenses: performance at scale (estimate the cost — "500 tickers × 252 days × 2 queries = 252k scans"), fidelity/information loss, audit trail / replayability, future signal extensibility, testability/isolation, idempotency, and schema/operational complexity. Drop dimensions that don't discriminate.
- Build the table. One row per option (or per dimension), one column per dimension, with a terse concrete cell per intersection — not "good/bad" but why ("re-fetch required", "O(1) lookup", "gone after run").
- Name the disqualifiers explicitly. For each rejected option, give the single sentence that kills it for long-term use: a one-way door (discards data you can't re-fetch), a constitution/principle violation (e.g. mutating an append-only audit table breaks replayability), or a known past failure (e.g. "same class of bug as the memoization emergency patch in 011").
- Recommend one, with the trade it accepts. State the winner AND what you're paying for it ("one extra table") so the choice is honest, not sold.
- Make it tunable where the right value is uncertain. If the decision hides a magic number (threshold, weight, window), promote it to a config field with a sensible default rather than hard-coding — note this in the recommendation.
- Record the decision in the artifact immediately — into whichever artifact set the project uses
(
../../runtime/references/spec-artifact-discovery.md): for the structured layout, the spec's Clarifications/Decisions section (orresearch.md); for the design-doc layout, the Decisions section of the design doc (docs/design/specs/*-design.md). Capture the chosen option and the one-line rationale so downstream planning and tasks inherit it. Keep field/entity names consistent with the rest of the artifact set — a rename here is a future cross-artifact finding.
04 同仓库更多 Skills
upstream-fix
Traces quality failures upstream to spec, rule, or workflow root cause. Proposes fixes at the right level.
triage
Dedup gate + batch-classify observations into five classes, enrich ARTIFACTs, batch-approve, delegate to intake/decision or queue.
sprint-planning
Sprint planning — story selection, team composition, Gherkin specs, and visual companion plan gate for developer sign-off.
sprint-manager
Sole writer of stories/index.json and sprints/index.json — validates state transitions, activates sprints, manages epic membership.
sprint-dev
Sprint execution — dependency-driven story development, post-merge AVFL, and team review.
retro
Sprint retrospective — transcript audit engine (dynamic Workflow), story verification, findings document, and sprint closure.