Loading...
Loading...
Found 4,154 Skills
Autonomous PRD implementation loop — turns GitHub issues into shipped code using TDD, code review gates, and Docker sandbox isolation. The execution engine for the grill-me → write-a-prd → prd-to-issues → ralph pipeline.
Read.ai platform help — meeting intelligence with engagement/sentiment analytics, Search Copilot across meetings/email/chat, Ada digital twin, REST API (beta) + MCP Server (`api.read.ai/mcp/`), OAuth auth, webhook automations (`meeting_end` events with HMAC signing), CRM sync to Salesforce/HubSpot, Zapier/n8n workflows, 20+ language transcription. Use when setting up Read.ai webhooks or API integration, connecting Read.ai transcripts to a CRM or data warehouse, configuring Read.ai engagement analytics for a sales team, comparing Read.ai pricing tiers, troubleshooting Read.ai auto-joining meetings without permission, or setting up the Read.ai MCP server with Claude or Cursor. Do NOT use for picking between note-takers (use /sales-note-taker) or reviewing a specific call for coaching (use /sales-call-review).
Genesys Cloud CX platform help — enterprise CCaaS with AI-powered experience orchestration, omnichannel ACD routing (voice + digital), Architect IVR/flow builder, workforce management (WFM forecasting/scheduling/adherence), quality management (evaluations/scoring), predictive routing, agent assist, virtual agents, outbound dialer, Interaction Analytics, AppFoundry marketplace (450+ apps), REST Platform API with OAuth 2.0 and 15 regional endpoints, deep Salesforce integration (CX Cloud joint product + Service Cloud Voice BYOT), 4 tiers CX1 $75/CX2 $115/CX3 $155/CX4 $240 per user/mo + telephony minutes. Use when setting up Genesys Cloud routing or Architect flows, WFM forecasting not matching actual volume, quality management evaluations not triggering coaching, dropped calls or audio quality issues, comparing Genesys pricing tiers, integrating Genesys with Salesforce or ServiceNow, Genesys reporting hard to navigate, MFA management confusing, Genesys API integration, or evaluating enterprise CCaaS platforms. Do NOT use for building a general coaching program (use /sales-coaching) or comparing CCaaS platforms (use /sales-ccaas-selection).
Use this skill when the user asks to call an authenticated HTTP API (for example "call the GitHub/OpenAI/Slack API", "hit an endpoint that needs a bearer token") and the `sesame` CLI is already installed on this device. The agent invokes `sesame request`, which forwards the HTTP call through the user's own broker and attaches the auth header server-side. The skill does not install software, does not read credentials from the environment, and runs shell only within the fixed `sesame` subcommand surface (`request`, `status`, `hostnames`, `login`, `refresh`). Skip for unauthenticated public endpoints, localhost services, or when the user has already exported a token in the environment for direct use.
Clone or update https://github.com/sxhzju/wechat-2d and render the default WeChat-style 2D chat motion video with Remotion. Use when users ask for 微信聊天动画, wechat 2d chat render, 微信视频消息动效, or exporting the default demo from the wechat-2d project.
Research GitHub, GitLab, and Bitbucket repositories using DeepWiki MCP server. Use when exploring unfamiliar codebases, understanding project architecture, or asking questions about how a specific open-source project works. Provides AI-powered repo analysis and RAG-based Q&A about source code. NOT for fetching library API docs (use fetching-library-docs instead) or local files.
Read and parse DLIS (Digital Log Interchange Standard) and LIS (Log Information Standard) well log files. Use when Claude needs to: (1) Read/parse DLIS or LIS files, (2) Extract well log curves as numpy arrays, (3) Access file metadata and origin information, (4) Handle multi-frame or multi-file DLIS, (5) Convert DLIS to LAS or DataFrame, (6) Work with RP66 format well logs, (7) Process array or image log data.
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.
Search the internet with Google or DuckDuckGo, inspect results, and extract selected pages as readable Markdown. Use when answers require current web sources, JavaScript-rendered pages, or browser access that can handle bot protection. Prefer dedicated tools such as GitHub CLI for GitHub data and curl for direct files or simple URLs.
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
Create OpenCode plugins using the @opencode-ai/plugin SDK. Use for building custom tools, event hooks, auth providers, or tool execution interception. Use proactively when developing new plugins in .opencode/plugin/ or ~/.config/opencode/plugin/. Examples: - user: "Create a plugin to block dangerous commands" → implement tool execution before hook with blocking logic - user: "Add a custom tool for jira" → design tool schema and implementation using SDK context - user: "Show toast on file edit" → react to file edit events and display status message - user: "Build a custom auth provider" → implement auth flow for new model provider - user: "Intercept git commits" → add hook to validate commit messages before execution
Deploy static sites to Cloudflare Pages with custom domains and CI/CD. Use when the user wants to deploy a site to Cloudflare Pages, add a custom domain to a Pages project, set up GitHub Actions CI/CD for Cloudflare Pages, roll back a deployment, or verify deployment status. Triggers on "deploy to Cloudflare", "Cloudflare Pages", "add custom domain", "pages deploy", or any Cloudflare Pages hosting workflow.