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Reviews code for bugs, style, and best practices. Use when reviewing PRs or checking code quality.
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Basé sur la classification professionnelle SOC
Extract creative intent from images into executable build specs. Activates on images + build intent, "image to mission", "i2m", or capturing visual energy in code/design.
Unit Circle Laboratory + sc-dev-team autonomous mission control. Provides human-in-the-loop automation layer, pipeline management, context lifecycle, stuck-state prevention. UC re-execution series and dev branch milestones. Adapted from uc-lab pattern for code plan/execute/verify/complete. Auto-activates during UC milestone work; trigger: user says 'bring up the dev team'.
Generate intelligence briefings for the planning dashboard. Use this skill whenever a request file appears in `.planning/console/inbox/pending/` whose `type` field starts with `intelligence.` (refresh_briefing, triage_finding, snapshot_diff, investigate_section, dismiss_finding). The skill reads the per-project KB at `.gsd/intelligence/intelligence.db`, synthesizes a briefing with a causal hypothesis + acknowledged uncertainty + confidence label and ranked moves, then writes the result back to the KB. Always trigger this skill for these request types — do not generate briefings manually.
Sketched Isotropic Gaussian Regularization primitive. Scalar loss matching the embedding distribution to a standard-normal target via Cramér-Wold slicing and the Epps-Pulley empirical characteristic function test. Port of rbalestr-lab/lejepa (MIT). Default-off in v1.49.571.
Adversarial spec-compliance PR review — cross-references diffs against approved specs, verifies runtime claims against source, detects competing PRs, audits scope/convention compliance. Use before merging.
Pick among candidate outputs (code, configs, plans) by running them on diverse inputs and clustering by behavioural fingerprint, rather than by textual aggregation or log-probability. Activates when an executor returns multiple plausible candidates that need disambiguation, when output-majority voting would be the default choice, or when reviewing generated code that has not yet been validated. The 2026 evidence (Semantic Voting, arxiv 2605.08680v1) is that any execution-based selector dominates output-majority voting by 19-52pp; sketch-generated inputs beat random fuzz by 11.3pp. Triggers: "pick the best candidate", "majority vote on code", "select from N samples", "validate the generated output", "behavioural verification".
| name | code-review |
| description | Reviews code for bugs, style, and best practices. Use when reviewing PRs or checking code quality. |
| version | 1.0.0 |
| format | "2025-10-02T00:00:00.000Z" |
| triggers | ["reviewing PRs or checking code quality"] |
| updated | "2026-04-25T00:00:00.000Z" |
| status | ACTIVE |
Correctness: Logic errors, edge cases, off-by-one, resource leaks, race conditions, error handling
Security: Input validation, injection (SQL/XSS), auth/authz, secrets exposure, CSRF
Performance: N+1 queries, redundant work, memory leaks, blocking I/O, missing indexes
Maintainability: Clear naming, single responsibility, DRY, test coverage
| Level | Action |
|---|---|
| CRITICAL | Security/data-loss risk — must fix |
| MAJOR | Bug/performance — should fix |
| MINOR | Code smell — consider fixing |
| STYLE | Formatting — optional |
### [SEVERITY] Brief description
**File:** path:line
**Issue:** What's wrong
**Suggestion:** Proposed fix
== true/false → use boolean directlycatch(e) {} → swallowed error