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Found 1,263 Skills
Comprehensive pre-merge validation checklist for Python/React pull requests. Use before approving or merging any PR. Covers code quality checks (linting, formatting, type checking), test coverage requirements, documentation updates, migration safety, API contract compatibility, accessibility compliance, bundle size impact, and deployment readiness. Provides a systematic checklist that ensures nothing is missed before merge. Does NOT cover security review depth (use code-review-security).
Semi-automated design quality review for Flows apps. Runs concrete repo probes (grep, lint, build) to propose a draft 1–5 score for each of the official 10 quality-guidelines questions from docs.cognite.com/cdf/flows/guides/quality-guidelines, then asks the user to confirm or override each score. Still requires the user to walk their tasks end-to-end in the running app (Step 2) since navigation and clickability feel cannot be measured statically. Writes reviews/design-review/feedback-round-<N>/design-review-report.md with an overall average and prioritized fix lists. Use when the user asks to run a Flows design review, run the design quality assessment, or run flows-design-review. Must be run AFTER flows-code-review reaches 0 Must Fix and BEFORE flows-external-app-submit.
Luban - Skill Polishing Workshop. Transform a "usable Skill" into a public Skill asset that is "understandable, installable, shareable, verifiable, and continuously evolvable". The methodology consists of five craftsman-like steps: 1. Material Inspection: First challenge whether the premise of this Skill is valid; directly state if the "material" is not worth polishing. 2. Peer Research: Search for similar Skills online to clarify its position in the ecosystem. 3. Dimension Measurement: Evaluate using three metrics - structure, actual testing, and live verification (live verification means reconciling with real running outputs; a green CI can be deceptive). 4. Iterative Refinement: Freeze the original version as a baseline; only retain changes that pass the verification gate, otherwise revert. Try to institutionalize verification methods as tools and rules in the repository. 5. Post-Release Iteration: Release is not the end; maintain a benchmark observation list, and start the next iteration based on real feedback. This tool is used when users want to upgrade, optimize, polish, productize, or release their self-developed Skills. The final deliverables include a structured Skill Polishing Report, directly replaceable rewritten segments, and a shareable "Graduation Certificate" result card that can be screenshot. Trigger phrases include but are not limited to: "Let Luban take a look at this skill", "Polish at Luban's Workshop", "Polish my skill", "Upgrade my skill", "Optimize this skill", "Skill check-up", "Skill audit", "Productize my skill", "How to release this skill", "Benchmark against similar skills", "Why no one installs my skill", "Help me publish my skill to GitHub/ClawHub", "Improve SKILL.md". Even if users only provide a Skill directory, GitHub repository link, or a segment of SKILL.md saying "Help me figure out how to modify it", it should be triggered as long as the context is about making the Skill more usable and shareable. Do NOT use this for creating a new Skill from scratch (use skill-creator), regular code review (use code-review), or rewriting ordinary prompts unrelated to Skill assets.
Defense-in-depth verification before declaring any task complete. Run tests, check build, validate changed files, verify no regressions. Applies 4-level adversarial artifact verification (EXISTS > SUBSTANTIVE > WIRED > DATA FLOWS) with goal-backward framing. Use before saying "done", "fixed", or "complete" on any code change. Use for "verify", "make sure it works", "check before committing", or "validate changes". Do NOT use for debugging (use systematic-debugging) or code review (use systematic-code-review).
Review code architecture for maintainability, catch structural issues before they become debtUse when "Reviewing pull requests with structural changes, Planning refactoring work, Evaluating new feature architecture, Assessing technical debt, Before major releases, When code feels "hard to change", architecture, code-review, refactoring, design-patterns, technical-debt, dependencies, maintainability" mentioned.
Orchestrate the full Platonic Coding workflow from conceptual design to RFC specs, implementation guides, code implementation, and spec-compliance review. Always shows current phase; uses interactive chat in Phase 0, invokes platonic-specs in Phase 1, platonic-impl-guide in Phase 2, coding agents in Phase 3, and platonic-code-review in Phase 4.
Refresh stale learning docs and pattern docs under docs/solutions/ by reviewing them against the current codebase, then updating, consolidating, replacing, or deleting the drifted ones. Trigger this skill when the user asks to refresh, audit, sweep, clean up, or consolidate stale docs in docs/solutions/ (phrases like "refresh my learnings", "audit docs/solutions/", "clean up stale learnings", "consolidate overlapping docs", "compound refresh", "/ce-compound-refresh"), or when ce-compound has just captured a new learning and flagged a specific older doc in docs/solutions/ as now inaccurate or superseded — invoke with the narrow scope hint ce-compound provides. Also trigger when the user points at a specific learning or pattern doc under docs/solutions/ and calls it stale, outdated, overlapping, or drifted. Do not trigger for general refactor, migration, debugging, or code-review work unless the user has explicitly directed attention to docs/solutions/ itself.
Go interface design patterns: implicit interfaces, consumer-side definition, interface compliance verification, composition, the accept-interfaces-return-structs principle, and common pitfalls. Use when designing interfaces, decoupling packages, defining contracts, reviewing interface usage, or refactoring for testability. Trigger examples: "design interface", "accept interfaces return structs", "interface compliance", "consumer-side interface", "interface composition". Do NOT use for HTTP handler patterns (use go-api-design) or general code review (use go-code-review).
Multi-language code quality gate with auto-detection and language-specific linters. Use when user asks to "run quality checks", "quality gate", "lint all", "check everything", "pre-commit checks", or "is this code ready to commit". Use for verifying code quality across polyglot repos. Do NOT use for single-language linting (use code-linting) or comprehensive code review (use systematic-code-review).
WHEN: Performance analysis, bundle size optimization, rendering, Core Web Vitals, code splitting WHAT: Bundle analysis + large dependency detection + re-render issues + useMemo/useCallback suggestions + LCP/FID/CLS improvements WHEN NOT: Code quality → code-reviewer, Security → security-scanner
Post-mortem diagnostic analysis of failed or stuck workflows. Detects stuck loops, missing artifacts, abandoned work, scope drift, and crash/interruption patterns through git history and plan file analysis. Produces a structured diagnostic report with anomaly confidence levels, root cause hypotheses, and recommended remediation. READ-ONLY: never modifies files. Use for "forensics", "what went wrong", "why did this fail", "stuck loop", "diagnose workflow", "post-mortem", "workflow failure", or "session crashed". Do NOT use for debugging code bugs (use systematic-debugging), reviewing code quality (use systematic-code-review), or fixing issues (forensics only diagnoses).
Create an isolated git worktree for parallel feature work or PR review. Use when starting work that should not disturb the current checkout, or when `ce-work` or `ce-code-review` offers a worktree option.