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Found 4,848 Skills
AI-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP, RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON parsing, structured finding output, OWASP mapping, and remediation guidance.
Scrape social media profiles, posts, comments, followers, and search across 6 platforms via x402. USE FOR: - Getting TikTok, Instagram, X/Twitter, Facebook, Reddit, or LinkedIn profiles - Fetching a user's posts, stories, highlights, or videos - Getting comments, replies, and reactions on posts - Listing followers and following for any account - Searching posts, hashtags, profiles, jobs, and ads across platforms - Cross-platform social media research and monitoring TRIGGERS: - "tiktok", "instagram", "facebook", "linkedin profile", "linkedin posts" - "get followers", "who follows", "following list" - "scrape profile", "get posts from", "social media data" - "instagram stories", "tiktok videos", "facebook page" - "linkedin company", "linkedin jobs", "linkedin ads" - "cross-platform", "social media research" IMPORTANT: StableSocial uses an async two-step flow. Step 1: POST triggers data collection (paid, $0.06). Step 2: Poll GET /api/jobs?token=... until finished (free). All endpoints are $0.06 per call. Use `npx agentcash fetch` for paid POST triggers. Use `npx agentcash fetch` for free GET polling. IMPORTANT: Use exact endpoint paths from the Quick Reference tables below. All paths include a platform prefix (e.g. `https://stablesocial.dev/api/tiktok/...`).
Scans the codebase against another skill's criteria using a parallel agent team. Use when the user says /scan <skill-name> to audit code quality, find violations, or assess conformance to best practices.
A software security skill that integrates with Project CodeGuard to help AI coding agents write secure code and prevent common vulnerabilities. Use this skill when writing, reviewing, or modifying code to ensure secure-by-default practices are followed.
Expert children's book writer creating delightful, engaging books for ages 2-9. Specializes in rhyming books, stories, songs with proper values, educational content, and age-appropriate language. Crafts books that captivate young readers while teaching important life lessons.
CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
Produces a single-story walkthrough of AI-authored code changes from runtime trigger to final behavior, weaving changed and unchanged code into one narrative with annotated diffs, trade-offs, alternatives, and risk analysis. Use when asked to "explain what changed", "walk me through this diff", "summarize agent edits", "show how this feature works", or "explain this implementation step by step".
Create, manage, and execute agent tools (claude, codex) inside Docker sandboxes for isolated code execution. Use when running agent loops, spawning tool subprocesses, or any task requiring process isolation. Triggers on "sandbox", "isolated execution", "docker sandbox", "safe agent execution", or when working on agent loop infrastructure.
Create Trae IDE rules (.trae/rules/*.md) for AI behavior constraints. Use when user wants to: create a project rule, set up code style guidelines, enforce naming conventions, make AI always do X, customize AI behavior for specific files, configure AI coding standards, or establish project-specific AI guidelines. Triggers on: 'create rule', '创建 rule', 'project rule', '.trae/rules/', 'AGENTS.md', 'CLAUDE.md', 'set up coding rules', 'make AI always use PascalCase', 'enforce naming convention', 'configure AI behavior'. Do NOT use for skills (use trae-skill-writer) or agents (use trae-agent-writer).
Systematically add test coverage for all local code changes using specialized review and development agents. Add tests for uncommitted changes (including untracked files), or if everything is commited, then will cover latest commit.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Provides structural context for downstream review and refactoring workflows. Use when before architecture reviews to understand file organization, exploring unfamiliar codebases to map structure, estimating scope for refactoring or migration. Do not use when general code exploration - use the Explore agent. DO NOT use when: searching for specific patterns - use Grep directly.