analyze
Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target>
Batch-validate ALL findings through the 7-Question Gate. Kills weak findings in bulk. Usage: /triage
Claude Code
$ npx -y skills add H-mmer/pentest-agents --skill triage --agent claude-code
Codex
$ npx skills add H-mmer/pentest-agents --skill triage -a codex -y
Cursor
$ npx skills add H-mmer/pentest-agents --skill triage -a cursor -y
Gemini CLI
$ npx skills add H-mmer/pentest-agents --skill triage -a gemini-cli -y
GitHub Copilot
$ npx skills add H-mmer/pentest-agents --skill triage -a github-copilot -y
OpenCode
$ npx skills add H-mmer/pentest-agents --skill triage -a opencode -y
Windsurf
$ npx skills add H-mmer/pentest-agents --skill triage -a windsurf -y
name: triage description: "Batch-validate ALL findings through the 7-Question Gate. Kills weak findings in bulk. Usage: /triage" disable-model-invocation: false
Batch triage all findings.
ALL validator agents dispatched by this command MUST use `model: "inherit"`.
1. Read findings.md and/or findings.json 2. List all findings with a numbered summary 3. For EACH finding, launch `validator` agent with the finding details 4. Collect results: PASS / KILL / DOWNGRADE / CHAIN REQUIRED 5. Output summary table:
TRIAGE RESULTS
═══════════════
# Finding Decision Reason
1 GraphQL schema leakage KILL Q7 Never-submit: introspection alone
2 Config exposure SayTech KILL Q7 SPA client config is by design
3 Internal service URLs KILL Q6 Not exploitable externally
4 IDOR on /api/users/{id} PASS Confirmed with real data
5 XSS on comments PASS Cookie theft PoC works
PASSED: 2 findings → ready for /report
KILLED: 3 findings → removed from queue6. Update brain with triage results 7. For KILLED findings: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py record <target> exhausted "<finding>" "<kill reason>"` 8. For PASSED findings: suggest `/report` or `/validate` for full PoC + evidence
Batch triage should reduce the queue aggressively.
For each finding, produce:
Do not average weak findings into a stronger story. Chain them only when one finding provides a capability the next finding consumes.
Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.
Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target>
Autonomous hunt orchestrator. INSATIABLE in --autonomous mode: enforces an EXHAUSTION CONTRACT (26 canonical hunter classes,…
Manage the engagement brain. Subcommands: 'init' to set up, 'brief <target>' for pre-flight, 'status' for overview, 'exhausted…
Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then…
Run the finding correlation engine to discover attack chains from individual findings.
Use for authorized security assessment of REST, GraphQL, WebSocket, or SOAP APIs, including discovery, authentication,…
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys)…
Clean and finalize authorized natural-language text intended for readers by auditing suspicious invisible Unicode and rewriting…