agentleFS
Sign inStart free
PthahnixPthahnix/De-Anthropocentric-Research-Engine/skills/cross-examine/SKILL.md

cross-examine

Skill504 starsChanged 51 days agoApache-2.0View on GitHub

Probe responses for inconsistency, logic gaps, and unsupported claims.

3 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

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    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:

    Ask targeted follow-up questions.

    line 17
  2. Distinctive:

    Do not treat refusal or verbosity as inconsistency without a claim-level comparison.

    line 27

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

cross-examine

Purpose

Probe responses for inconsistency, logic gaps, and unsupported claims.

Input contract

required: [claim, response, questions, evidence]
optional: [criteria, prior_rounds]
constraints: [questions must target explicit claims or assumptions]

Procedure

  1. Identify unsupported or inconsistent assertions.
  2. Ask targeted follow-up questions.
  3. Record answers, unresolved gaps, and evidence requests.

Output contract

produces: [cross_examination_record, inconsistency_findings, evidence_requests]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Each question maps to a claim, premise, or inference step.

Failure and counterexamples

Do not treat refusal or verbosity as inconsistency without a claim-level comparison.

Provenance map

  • resolved: cross-examination

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.

Check your setup, free