Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/0dayinc/pwn/policynpx skills add 0dayInc/pwn --skill policygit clone --depth 1 https://github.com/0dayInc/pwnWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/0dayinc/pwn/policy)<a href="https://agentmods.dev/skills/0dayinc/pwn/policy"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/policy.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00020 | $0.00669 |
| Opus 5 | $0.00010 | $0.00334 |
| Sonnet 5 | $0.00004 | $0.00134 |
| Haiku 4.5 | $0.00002 | $0.00067 |
Grade A, and why
pwn-ai-agent-policy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PWN::AI::Agent::Policy
PWN::AI::Agent::Policy is the LIVE tabular RL controller that pwn-ai did not have before R5. Everything else in the harness is retrieval-plus-policy: scores are written to disk and re-injected as prose, or exported later for optional LoRA. This module is the missing MDP: state s — discretized (kind, task, plan, completeness, usable, last, fail) action a — tool name, or "final" reward r — step: 0 (spam cost −0.01 after 8 tools); terminal: judge × confidence next s' — state after the tool result Each Loop turn is one episode. Transitions land in ~/.pwn/policy_traj.jsonl. Q(s,a) and REINFORCE logits H(s,a) are updated from those tuples and persisted in ~/.pwn/policy.json. The learned Q values are an ADVISORY term in Registry.rank. They never replace TaskSummarizer planning, plan_first, or CORE_TOOLS. Disable with PWN::Env[:ai][:agent][:policy] = false.
When to use
Call PWN::AI::Agent::Policy from pwn_eval when the task needs this module.
Do not reimplement it in shell.
Methodologies
Generated from pwn/ai/agent/policy.rb. Prefer the public class methods below.
Class methods take (opts = {}) and read opts.
How to call
PWN::AI::Agent::Policy.help
PWN::AI::Agent::Policy.state(opts)
Public methods
statecoldwarmepisode_budget_metbegin_episodeobserve_stepfinishupdate_qupdate_pgqvalueadvantagerecommendcurrent_statecurrent_episodedetach_episodeattach_episodeloadsavetrajectoriesstatsevaluateto_contextleanresetenabledauthorshelpwarmupmaybe_warmupattach_episode!cold?detach_episode!enabled?episode_budget_met?lean!maybe_warmup!update_pg!update_q!warm?warmup!
Source
pwn/ai/agent/policy.rb
Verification
PWN::AI::Agent::Policy.respond_to?(:state) after the
module is loaded. Read the source for parameter names.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 86 lines · 20 tokens per session scan A 157cd8dda71b
pwn-ai-agent-policy is a skill published in the GitHub repository 0dayInc/pwn (78 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 669 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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