agentleFS
jpoindexterjpoindexter/ai-agent-skills/adversarial-verify/SKILL.md

adversarial-verify

Skill1 starsChanged 5 months agoMITView on GitHub

Send a diff or output to a skeptic agent tasked with refuting it. Surface only findings the skeptic can defend with file:line evidence. Default posture is "not real" — findings must earn their place.

7 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    After producing output (a shipped card, a security audit, a bug report, a spec), send it to a skeptic agent whose job is to REFUTE each …

    line 7
  2. Distinctive:

    Keep only findings the skeptic confirmed with file:line.

    line 21
  3. Distinctive:

    No file:line evidence = finding is rejected, regardless of how plausible it sounds.

    line 27
  4. Distinctive:

    Do not ask the same agent that produced the output to self-verify — use a separate agent context.

    line 28
  5. Distinctive:

    Run after each shipped card:

    line 44

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Adversarial Verify

After producing output (a shipped card, a security audit, a bug report, a spec), send it to a skeptic agent whose job is to REFUTE each finding. Only confirmed findings with file:line evidence survive.

Steps

  1. Collect the output to verify: a diff, a list of findings, a written spec, or a draft.
  2. Spawn a skeptic agent with this brief:
    Your job is to REFUTE the following findings. Default posture: not real.
    For each finding, either:
    - Confirm it with file:line evidence (the only way it survives), or
    - Refute it with a specific reason (misread, already handled, wrong file, etc.)
    Do not hedge. Pick a side per finding.
  3. Collect the skeptic's verdicts.
  4. Keep only findings the skeptic confirmed with file:line.
  5. Fix confirmed findings, then re-run the base gate (typecheck + tests + build).

Constraints

  • A dropped or failed skeptic connection = "review incomplete" — re-run, never assume pass.
  • No file:line evidence = finding is rejected, regardless of how plausible it sounds.
  • Do not ask the same agent that produced the output to self-verify — use a separate agent context.
  • For 3+ findings, run skeptic agents in parallel (one per finding).

Report format

Findings submitted: <n>
Confirmed (with evidence): <n>
  - <finding> — <file:line> — <what to fix>
Refuted: <n>
  - <finding> — <reason rejected>
Review status: complete | incomplete (skeptic dropped — re-run)

Loop usage

Run after each shipped card:

/loop after each shipped card, run /adversarial-verify on the diff before moving on.

Or as a one-shot pre-merge check:

Verify this diff adversarially before I merge.

Scaling

  • 1–3 findings: one skeptic handles all.
  • 4+ findings: one skeptic per finding in parallel; require majority confirmation (≥2/3) to surface.
  • Security audit: use 3 independent skeptics per finding; require all 3 to confirm.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.