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Found 6,679 Skills
Security audit and vulnerability scanner for AI agent skills before installation. Use when: (1) evaluating a skill from an untrusted source, (2) auditing a skill directory or git repo URL for malicious code, (3) pre-install security gate for Claude Code plugins, OpenClaw skills, or Codex skills, (4) scanning Python scripts for dangerous patterns like os.system, eval, subprocess, network exfiltration, (5) detecting prompt injection in SKILL.md files, (6) checking dependency supply chain risks, (7) verifying file system access stays within skill boundaries. Triggers: "audit this skill", "is this skill safe", "scan skill for security", "check skill before install", "skill security check", "skill vulnerability scan".
Investment-banking pitch book for strategic alternatives — trading comps, precedent transactions, valuation football field, DCF sensitivity, strategic-options matrix, process recommendation. Built by adapting `assets/template.html` so IB-specific chrome, disclosure bands, and source labels are preserved. Use for Board / sell-side discussion materials. Not a VC fundraising deck (see html-ppt-pitch-deck). Workflow adapted from Anthropic financial-services Pitch Agent (Apache-2.0).
Write, rewrite, or normalize structured `*.spec.md` specification files for agent-driven development. Use this whenever the user asks for a spec, requirements, acceptance criteria, implementation-ready documentation, feature definition before coding, or wants an existing idea/codebase turned into an actionable spec, even if they do not explicitly say "spec".
Manage GitHub pull request workflows for coding agents. Use when Codex needs to open, update, monitor, or hand off a PR; wait for CI checks or reviewer feedback; inspect unresolved review threads; address requested changes; summarize PR status; or decide whether to continue, wait, report a timeout, or ask for human input.
Convert a local AGENT.md into a Claude Code optimized agent. Audits one agent against Claude Code runtime behavior, creates a per-agent DAG rewrite plan with source-backed guardrails, and optionally rewrites the frontmatter and system-prompt body so the agent is thinner, more role-specific, and better aligned with Claude's agent runtime. Use when the user says "convert this agent to Claude", "normalize this AGENT.md", "thin this agent", or "rewrite this persona for Claude Code".
Create implementation task plans in `_/local-plans/<plan-name>.md`. First investigate the codebase using the Explore Agent, then document it in verifiable granularity and parallel-executable units, following the standard format (Background & Purpose, Current Status, Design, File Structure Tree, Implementation Steps, Verification Methods) that can be validated by the plan-verifier Agent. Used for requests like "Make a plan", "Design", "Task decomposition", "Think about implementation approach". plan, planning, design, implementation plan, task decomposition, create-plan
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Implement the Business Brain pattern. Gives every agent skill access to your tone, audience, and positioning without bloating the context window. Use when asked for brand context, voice, or positioning, or when setting up a new project's brain.
Teaches the agent to produce D3 charts and interactive data visualizations. Useful for editorial dashboards, reports, and explanatory graphics.
Create and manage Jenkins CI/CD pipelines, configure agents, manage plugins, and automate builds. Use when working with Jenkins servers, creating Jenkinsfiles, or setting up build automation for enterprise environments.
Generate and use command-line interfaces that make any software controllable by AI agents with structured JSON output
Desktop GUI companion for Hermes Agent - install, configure, chat with AI assistant featuring tool use, memory, skills, and multi-platform messaging