Most AI agents can generate commands but lack domain playbooks. This library supplies 754 production-style cybersecurity skills encoded for sub-second discovery and stepwise execution, letting agents follow the same decision logic a senior analyst would use during hunts, forensics, and incident response.
What Sets It Apart
- Five-framework mapping: each skill is cross-referenced to MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND and NIST AI RMF, so agents can reason about offense, defense, and AI-specific risk in one lookup. This reduces manual crosswalk work when producing compliance or mitigation recommendations.
- Agent-native format: skills use agentskills.io frontmatter + structured Markdown so agents can scan frontmatter (~30 tokens) for relevance and load full workflows (500–2000 tokens) only when needed. This progressive disclosure keeps context windows efficient.
- Practitioner workflows rather than scripts: skills encode when to run a technique, prerequisites, verification steps and mapping to frameworks — not just command snippets — enabling higher-fidelity automation and traceable outputs for analysts.
- Broad compatibility: designed to be consumed by Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI and any agentskills.io-compatible platform, enabling reuse across agent runtimes.
Who It's For & Trade-offs
Great fit if you: integrate agentic assistants into SOC workflows, build agent-based DFIR or threat-hunting pipelines, or research agent behavior with realistic operational tasks. The repo accelerates agent capability-building and framework-aligned reporting. Look elsewhere if you: need vetted, enterprise-certified playbooks or vendor-specific integrations out of the box — this is a community-maintained library that requires validation in target environments. It provides procedural guidance, not executable exploit tooling or turnkey orchestration. Users must verify commands, tool versions, and legal/ethical constraints before automated execution.
Where It Fits
Use this alongside SIEM rules, ATT&CK layers, and runbooks: treat the skills as the decision and verification layer that tells an agent which tools and checks to run and how to interpret results. It complements code-centric security repos by focusing on structured operational knowledge rather than payloads or single-tool automations.
