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/mistakesnpx skills add 0dayInc/pwn --skill mistakesgit 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/mistakes)<a href="https://agentmods.dev/skills/0dayinc/pwn/mistakes"><img src="https://agentmods.dev/badge/skills/0dayinc/pwn/mistakes.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 5.1 | $0.00023 | $0.00730 |
| Opus 5 | $0.00012 | $0.00365 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
pwn-ai-agent-mistakes 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 today.
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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PWN::AI::Agent::Mistakes
PWN::AI::Agent::Mistakes is the negative-feedback half of the pwn-ai learning loop. Where Learning records WHAT WORKED and Metrics records HOW OFTEN a tool worked, Mistakes records SPECIFIC FAILURE PATTERNS with a stable fingerprint so the agent can (a) recognise it is repeating itself, (b) be told exactly what not to do again in every future system prompt, and (c) capture the FIX once one is found so the avoidance lesson becomes an actionable correction. A "mistake" is keyed by sha12(tool + normalised_error). Normalisation strips volatile bits (paths, hex addresses, line numbers, timestamps, UUIDs, PIDs) so "NoMethodError ... at foo.rb:42" and "... at foo.rb:99" collapse to one signature and its :count climbs — that count IS the repeat detector. Closed loop (why it does NOT repeat mistakes): Loop.run --(tool failure)---------> Mistakes.record (persist + count++) Loop.run --(same sig fails ≥N)----> guard_repeated_failure (uses PERSISTENT count, so triggers on the 1st recurrence in a new session, not the 3rd) Loop.run --(failure w/ known fix)-> inline "KNOWN FIX: …" (self-corrects next iter) Loop.run --(user says "wrong")----> check_user_correction (flip last outcome + record) PromptBuilder <-------------------- Mistakes.to_context (DO-NOT-REPEAT + KNOWN-FIXES) model --(tool call)---------------> mistakes_record / mistakes_resolve
When to use
Call PWN::AI::Agent::Mistakes from pwn_eval when the task needs this module.
Do not reimplement it in shell.
Methodologies
Generated from pwn/ai/agent/mistakes.rb. Prefer the public class methods below.
Class methods take (opts = {}) and read opts.
How to call
PWN::AI::Agent::Mistakes.help
PWN::AI::Agent::Mistakes.load(opts)
Public methods
loadsavesignatureerror_classfamilyfindfor_toolrecordresolvetopextinguishextinguish_parkedparkoperator_inboxto_contextcorrection_hintnote_hint_outcomecorrectioncheck_user_correctionleanreseteffective_countauthorshelpcorrection?extinguish!extinguish_parked!lean!
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.
- today Changed · +2 lines 1ca564c49e71
- 2d ago Changed · +1 lines 28a30134b6e0
- 6d ago First seen · 70 lines · 23 tokens per session scan A 08da95820c6d
pwn-ai-agent-mistakes is a skill published in the GitHub repository 0dayInc/pwn (78 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 730 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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