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Found 1,270 Skills
Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
Evaluate agents and skills for quality, completeness, and standards compliance using a 6-step rubric: Identify, Structural, Content, Code, Integration, Report. Use when auditing agents/skills, checking quality after creation or update, or reviewing collection health. Triggers: "evaluate", "audit", "check quality", "review agent", "score skill". Do NOT use for creating or modifying agents/skills — only for read-only assessment and scoring.
Overview The TikTok Agent allows users to extract data from TikTok, including video metrics, creator profiles, and hashtag velocity, to bypass the limitations of manual trend-spotting. With the TikTo
Create new Claude Code skills with proper structure, YAML frontmatter, and best practices. Use when creating reusable knowledge modules, adding specialized guidance, or building domain-specific expertise.
Generate AGENTS.md file and docs/ knowledge base skeleton in the project root directory, and establish a document governance system for agent-first repositories. Manually triggered, writes the template after checking for existence.
Blockchain RPC and data access via Quicknode. Use when an agent needs to read onchain data (balances, token prices, transaction status, gas estimates, block data) across Base, Ethereum, Polygon, Solana, or Unichain. Supports both API key access and x402 wallet-based pay-per-request access with no account needed. Triggers on mentions of RPC, blockchain data, onchain queries, token balances, gas estimation, block number, transaction receipt, Quicknode, or x402.
Find prompt and model quality issues using real conversation data, with specific optimization recommendations. Can implement prompt fixes and model switches directly in your codebase.
Agent skill for agentic-payments - invoke with $agent-agentic-payments
Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.
Breaks natural-language problem descriptions into sub-tasks suitable for DAG nodes. The entry point of the meta-DAG. Identifies phases, dependencies, parallelization opportunities, and vague/pluripotent nodes that can't yet be specified. Uses domain meta-skills when available. Activate on "decompose task", "break down problem", "plan workflow", "what are the steps", "sub-tasks", "task breakdown". NOT for executing the decomposed tasks (use dag-runtime), building the DAG structure (use dag-planner), or matching skills to nodes (use dag-skills-matcher).
Improve an existing prompt or skill with targeted, minimal-diff edits that preserve its core intent, and return the revised artifact plus a short changelog and tradeoffs note. Use this whenever the user wants to refine, sharpen, tighten, or upgrade an existing prompt or skill, asks to "make it better," or wants a small high-leverage edit instead of a full rewrite — even if they don't explicitly mention tuning.
Onboarding guide for new team members in the agile flow with AI. Use when someone new joins the team and needs to understand how the planning, execution, and tracking flow works with AI agents.