Loading...
Loading...
Found 1,173 Skills
Generate a single-file interactive HTML code-review artifact for a GitHub PR. Fetches the diff via the gh CLI, performs an honest severity-coded self-review, and renders an artifact with: collapsible per-file diffs with colored inline annotations, severity filter chips, per-finding checkboxes, and a "Create feedback prompt" modal that aggregates the checked items into a paste-ready follow-up prompt ending with "Please address this feedback. Address each individual item in its own conventional commit." Use this skill whenever the user wants to review a pull request visually, asks for an HTML or static review artifact, says "review PR", "review this PR", "build a PR review", wants color-coded findings, feedback aggregation, or a review file they can share — even if they don't explicitly say "HTML". Also trigger on "code review artifact", "interactive review", "feedback prompt for a PR", or when the user mentions reviewing a specific PR number.
Detect AI-generated code patterns ("slop") in PHP/Laravel and TypeScript/React source — comment narration, generic naming, premature interfaces, defensive overdose, mock-everything tests, and the absence of human "scars". Use when reviewing AI-assisted PRs, auditing code for taste/quality (not metrics — that's technical-debt), or hardening a code-review checklist. Triggers on "review for AI slop", "find AI patterns", "check code feels human", "audit code-quality taste".
Third-party Claude Code token/context/code-review tools. Use when choosing or recommending an external tool to reduce token usage, manage context, or review large codebases.
Emulate supported AI code-review GitHub Actions locally and print a terminal-only review from portable skill instructions. Use when running /review-action or checking local PR-review feedback before publishing.
AFK adversarial code-review loop: Cursor agent CLI critic (grug + thermo-nuclear) produces structured findings; Codex validator confirms or pushbacks on regression risk; parent adjudicates and commits fixes per finding until clean. Config at ~/.config/adversarial-review/config.toml. Use for adversarial review, clean code loop, or unattended branch hardening.
Automate 7-phase feature development with specialized agents (code-explorer, code-architect, code-reviewer). Use for multi-file features, architectural decisions, or encountering ambiguous requirements, integration patterns, design approach errors.
Personalized 1-on-1 AI tutor using Bloom's 2-Sigma mastery learning. Guides users through any topic with Socratic questioning, adaptive pacing, and rich visual output (HTML dashboards, Excalidraw concept maps, generated images). Use when user wants to learn something, study a topic, understand a concept, requests tutoring, says 'teach me', 'I want to learn', 'explain X to me step by step', 'help me understand', or invokes /sigma. Triggers on: learn, study, teach, tutor, understand, master, explain step by step.
Create high-quality, production-grade skills for Claude Code. Expert guidance on skill architecture, workflow design, prompt engineering, and packaging. Use when user wants to create a new skill, build a skill, design a skill, write a skill, update an existing skill, improve a skill, refactor a skill, debug a skill, or package a skill. Triggers: 'create skill', 'build skill', 'new skill', 'skill creation', 'write a skill', 'make a skill', 'design a skill', 'improve skill', 'package skill', 'skill development', 'skill template', 'skill best practices', 'write SKILL.md'.
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.
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.
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.