Skill
analyze
Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target>
@h-mmerView SkillSecurity
Skill
/cost
Show cost tracking and ROI for this engagement.
Install
$ npx -y skills add H-mmer/pentest-agents --skill cost --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/cost
Context preview
The summary Claude sees to decide when to auto-load this skill.
Show cost tracking and ROI for this engagement.
SKILL.md
cost.SKILL.mdname: cost description: "Show cost tracking and ROI for this engagement." disable-model-invocation: false
Show engagement cost data.
Run these in sequence: 1. `uv run python3 $CLAUDE_PROJECT_DIR/tools/cost.py summary` 2. `uv run python3 $CLAUDE_PROJECT_DIR/tools/cost.py roi` 3. Provide analysis: which agents consumed the most, whether the spend is justified by findings.
Top-Tier ROI Review
Cost review is a hunting control, not accounting trivia.
- Segment spend by phase: recon, ranking, hunting, validation, reporting, rework.
- Flag any agent class with high spend and low durable output: no new surface, no killed hypotheses, no confirmed evidence.
- Compare spend to expected value: bounty range, report probability, duplicate risk, and remaining proof work.
- Recommend one concrete budget move: continue, pivot class, reduce parallelism, raise min-score, skip noisy targets, or run a focused chain pass.
- Treat repeated false positives as a training signal. Link the spend spike to `/learn`, `/brain`, or rules updates.
Ships withpentest-agents
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.
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172
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Maintained
Maintenance
Python
Language
3mo ago
Last commit
5mo ago
Created
Repo: H-mmer/pentest-agents
Other skills on pentest-agents.
@h-mmerView SkillSkill
autopilot
Autonomous hunt orchestrator. INSATIABLE in --autonomous mode: enforces an EXHAUSTION CONTRACT (26 canonical hunter classes, surface probe A-I, depth-engine…
@h-mmerView SkillSkill
brain
Manage the engagement brain. Subcommands: 'init' to set up, 'brief <target>' for pre-flight, 'status' for overview, 'exhausted [target]' to see dead ends.
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chain
Build deep exploit chains — dispatches chain-builder agent. Given bug A, recursively walks the chain graph. Usage: /chain (then describe bug A)
@h-mmerView SkillSkill
correlate
Run the finding correlation engine to discover attack chains from individual findings.
@h-mmerView Skill