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Found 17 Skills
Use when iterative review-fix cycles are needed on a plan or implementation — bounded loop with severity gating, automatic fixes, and finding disposition.
Shepherd a GitHub pull request all the way to merge-ready by relentlessly polling status and only acting once all automatic reviewers have finished. NEVER merges without explicit human approval. Use when the user says things like "shepherd this PR", "babysit this PR", "get this PR merge-ready", "wait for Cubic", "wait for Bugbot", or asks to drive a PR through review.
Reviews DataHub connector implementations against 22 golden standards for compliance, code quality, silent failures, test coverage, type design, and merge readiness. Use when reviewing connector code, checking a PR, auditing a connector implementation, or verifying connector standards compliance.
10-parallel code/design review using reviewer subagents. Use when: - Running code reviews on PRs, commits, or branches - Running design reviews on issues or documents - Need multi-perspective review (security, architecture, code, QA, historian)
Use when validating subjective quality criteria that cannot be deterministically tested — applies LLM-based evaluation with structured rubrics for tone, aesthetics, UX feel, documentation quality, and code readability. Triggers: documentation quality check, error message tone review, UX copy evaluation, code readability assessment, design aesthetic review.
Eight-axis judgment code review for the current diff — Correctness, Simplification, Tests, Documentation, Style, Intent, Design/API, Performance (+ Coherence on metadata changes). Five-phase pipeline scope → deterministic tool battery (npx/uvx-preferred, zero-install for the JS + Python majority) → 8 parallel LLM axis reviewers → Haiku validators on sub-80 findings (verbatim rubric, ≥80 threshold) → synthesis with no-silent-drop + Conventional Comments JSONL. Every report closes with "What I did NOT check" (security → /security-review, runtime perf, flaky detection). Opt-in flags `--verify-build`, `--mutation-test`, `--reconcile`, `--apply-safe`. Public-skill posture — zero auto-install, graceful skip on missing native tools.
Multi-agent quality improvement review with constructive feedback. Provides suggestions for best practices, code quality, alternatives, and performance optimization.
Use this skill when orchestrating multiple review types. Use when general review needed without knowing which specific skill applies, full multi-domain review desired, integrated reporting needed. Do not use when specific review type known - use bug-review, test-review, etc. DO NOT use when: architecture-only focus - use architecture-review.
Used for reviewing GitCode PRs, generating in-depth review conclusions or publishing line-by-line comments by combining PR metadata, diffs, and the context of the entire code repository. It is used when users want to review a GitCode PR, check a GitCode PR link, analyze change risks, or publish review comments to a GitCode PR. Typical trigger phrases include "review this PR", "inspect this PR", "check PR", or directly providing a GitCode PR link, such as https://gitcode.com/owner/repo/pull/123.
Deep clause-by-clause NDA review from Recipient or Discloser perspective. Produces issue log with redlines, fallbacks, rationales, owners, deadlines. Use when reviewing NDAs for negotiation or approval.
Iteratively reviews and fixes Claude Code skill quality issues until they meet standards. Runs automated fix-review cycles using the skill-reviewer agent. Use to fix skill quality issues, improve skill descriptions, run automated skill review loops, or iteratively refine a skill. Triggers on 'fix my skill', 'improve skill quality', 'skill improvement loop'. NOT for one-time reviews—use /skill-reviewer directly.
Autonomous workflow execution pipeline with CSV wave engine. Session discovery → plan validation → IMPL-*.json → CSV conversion → wave execution via spawn_agents_on_csv → results sync. Task JSONs remain the rich data source; CSV is brief + execution state.