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Found 2,684 Skills
Probe, transcript, and download video/audio with yt-dlp CLI on supported hosts. Use when you need metadata, captions, or local media. Transcript-first (probe, transcript, download). NOT for static HTML (Fetch MCP), research, or ffmpeg transforms.
Audit harness configs, discover gaps, usage signals, apply approved fixes. Use when tuning Claude, Codex, Copilot, Cursor, Gemini, Grok, OpenCode, Cherry, or LM Studio. NOT agents, MCP, or app telemetry.
Extract plain text from a document file - PDF, DOCX, XLSX, PPTX, RTF, or plain text/markdown/HTML. Use when a binary document needs to be turned into text, for example a contract PDF or an EHR DocumentReference attachment. Other skills (fhir) invoke scripts/extract.ts directly; the contracts MCP server bundles its own copy (servers/documents/src/extract.mjs) so its bundle stays self-contained — port fixes to both.
Use this skill when an MCP tool fails AND the introspection skill could not resolve the problem. This is the last-resort fallback (Tier 3): call the Pipefy GraphQL API directly using curl or httpx, authenticating with the Service Account (OAuth2) or a Personal Access Token (PAT) available as env var. Follow the 3-tier resolution strategy before reaching this point.
Pongfi Research is a cross-platform social media research Skill for any track. By dynamically discovering and calling TikHub MCP / public social data tools, it completes trend discovery, sub-track segmentation, competitive research, account auditing, viral content breakdown, comment demand mining, content gap identification, cross-platform comparison, and data-driven topic selection for industries, categories, brands, products, people, accounts, or topics. It supports public social platform data from Douyin, TikTok, Xiaohongshu, Instagram, YouTube, X, Weibo, Bilibili, Reddit, Kuaishou, Zhihu, WeChat, LinkedIn, Threads, etc.
Watch a topic list for anomalous heat spikes and push channel-formatted alerts (飞书/钉钉/企业微信/Telegram/Slack/Bark/ntfy/Email/Webhook) via trendradar MCP. Use when the user wants 异动告警/突发热点推送/监控 XX 话题/订阅热点/breakout alert/ping me when X spikes.
Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASE_URL injected automatically and compute that runs next to your data. Use when a user wants to host an API, an AI agent with long streaming responses, a WebSocket or server-sent-events (SSE) server, a webhook handler, a Discord bot, an MCP server, or any request/response workload that risks timing out on short, lambda-style serverless functions — and wants it to branch with their database. Triggers include "serverless function", "deploy an API", "long-running function", "streaming agent", "SSE server", "WebSocket server", "webhook handler", "MCP server", "run code next to my database", "function that won't time out", "function logs", "Neon Functions", and "Neon Compute".
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention building a chatbot with Sanity, creating an AI assistant for their content, setting up the Sanity Context MCP server, integrating Sanity with Claude/GPT/any LLM, making content searchable by AI, implementing semantic search over Sanity data, or connecting their CMS to an AI agent.
Slice an epic (with its architecture decisions) into PIV-sized tickets with a dependency graph, then create them in your tracker (Jira via the Atlassian MCP, or GitHub/Linear/local). Accepts the epic and its architecture as one doc or as an epic plus a separate linked architecture page. Turns a large strategic doc into the discrete units of work that the PIV loop consumes.
Guided, file-by-file PR review where the user controls the pace. Fetches the PR diff and metadata (using gh CLI, GitHub MCP, or local git fallbacks), sorts all changed files by number of lines (smallest first), and reviews them one-by-one as the user says "next". For each file it shows the diff, reads relevant surrounding context from the codebase (callers, schemas, tests) only when needed to confirm a bug, then gives a concise analysis and verdict. Flags real defects inline with exact fix proposals. Respects project-specific PR_REVIEW_INSTRUCTIONS.md rules when present. Use this skill whenever someone wants to review a GitHub PR interactively, step through a PR file by file, or do a guided code review of a pull request. Also triggers on "review pr", "sequential review", "file by file review", or "let's review this PR together".
Design ObjectStack AI skills, tools, knowledge sources, conversations, model registry entries, and MCP integrations. Use when the user is adding `*.skill.ts` / `*.tool.ts`, configuring an LLM provider, wiring agent tools, or indexing ObjectStack data as a knowledge source for RAG. Agents themselves are platform-internal (`ask` / `build`) — third parties extend them via skills and tools, not by authoring `*.agent.ts`. Do not use for general LLM prompting questions unrelated to ObjectStack metadata.
Reference for the uploads CLI and its stdio/hosted MCP tools — exact flags, keys, and contracts for put and attach, screenshot capture, stable PR/issue keys, the managed attachments comment, metadata and search, galleries, config defaults, login/doctor, and output formats. Use when driving the `uploads` CLI or its MCP tools (including the hosted MCP at agents.uploads.sh for agents without local filesystem/git access), when you need a public URL for a local file ("upload this", "host this image", "give me a public URL for this file"), when the CLI itself prints a hint or nudge you need to act on (a `hint` field in `--format json`, or the stderr note suggesting `--pr`/`attach --branch`), or when you need exact flags, key layouts, or setup and auth details. For the when-and-how of getting a screenshot or recording into a GitHub PR or issue, start with the github-screenshots skill — it defers here for CLI detail.