Purpose
Read recon/summary.json together with bug-hunting skill files and ask an
LLM to rank targets by likely impact and exploitability. A second pass
reasons about exploit chains across the ranked findings.
Anthropic is preferred when ANTHROPIC_API_KEY is set; otherwise the tool
falls back to local Ollama.
Output
recon/priorities.md— human-readable ranked notes appended per run.recon/priorities.json— latest structured priority list.recon/chain-analysis.mdandrecon/chain-analysis.json— exploit-chain hypotheses and missing-evidence notes for follow-up testing.
CLI
ai-prioritize acme-bounty
ai-prioritize acme-bounty --model sonnet-4-6 --ollama-model llama3.2
Notes
- The output is advisory. It does not replace scope checks or manual validation.
- Probe-report evidence is included when present and treated as untrusted
data inside
<probe_report>blocks. - See mg-harness
chain.readfor the AI-callable read endpoint over the chain analysis artifacts.