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 skills add ralfyishere/rules-with-receipts --skill adversarial-verifygit clone --depth 1 https://github.com/ralfyishere/rules-with-receiptsWrote 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/ralfyishere/rules-with-receipts/adversarial-verify)<a href="https://agentmods.dev/skills/ralfyishere/rules-with-receipts/adversarial-verify"><img src="https://agentmods.dev/badge/skills/ralfyishere/rules-with-receipts/adversarial-verify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ralfyishere/rules-with-receipts/adversarial-verify"><img src="https://agentmods.dev/badge/skills/ralfyishere/rules-with-receipts/adversarial-verify.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00123 | $0.01493 |
| Opus 5 | $0.00062 | $0.00746 |
| Sonnet 5 | $0.00025 | $0.00299 |
| Haiku 4.5 | $0.00012 | $0.00149 |
Grade A, and why
Adversarial Verify 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 10d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Verify
Purpose
Switch from author to attacker before the user does. Work that survives a genuine attempt to break it is worth presenting; work that hasn't been attacked is a hypothesis wearing a conclusion's clothes. This is a short, targeted pass — minutes, not a second project.
When to use this skill
- Before presenting any High/Critical-tier deliverable (per
effort-calibration). - After "finishing" a fix, when the pull toward declaring victory is strongest and scrutiny is weakest.
- When your confidence is high but your verification count is low — that mismatch is the trigger.
- Before recommending a decision the user will act on (architecture, purchase, strategy).
When NOT to use this skill
- Low-tier tasks and simple factual answers — one sanity check suffices.
- Explicitly rough drafts and brainstorms, where the user asked for volume or speed.
- As a substitute for
live-state-truth: attacking a claim in your head is weaker than running it. If a check is executable, execute it.
Operating procedure
Step 1 — Finish the draft first. Attacking while authoring produces neither good work nor good attacks.
Step 2 — Switch roles. You are now a skeptical senior reviewer whose job is to find the flaw. Assume there is one.
Step 3 — Run the attack list (pick the 3+ most relevant; don't run all mechanically):
| Attack | Question |
|---|---|
| Hidden assumption | What am I treating as true that I never checked? |
| Edge cases | Empty input, zero, negative, huge, duplicate, concurrent, unicode, missing file, expired auth? |
| Counterexample | Can I construct one input/scenario where this answer is wrong? |
| Wrongness probe | "What would have to be true for this to be wrong?" — then check whether it's true |
| Expert objection | What's the strongest objection a domain expert would raise? |
| Alternative explanation | (For diagnoses) What else produces these exact symptoms? |
| Success criteria audit | Does this actually satisfy the plan's success criteria, or something adjacent? |
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.
- 10d ago First seen · 81 lines · 0 tokens per session scan A bfa745bd4e15
Adversarial Verify is a skill published in the GitHub repository ralfyishere/rules-with-receipts (2 stars, last pushed 2mo ago), licensed MIT. It adds 123 tokens to every session and 1,493 once invoked, about $0.0006 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 2026-08-31.
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