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Think red team light

Skill product-on-purpose/thinking-framework-skills/skills/think-red-team-light

Evidence-graded, agent-executable thinking-method skills - 56 frameworks reduced to their working mechanism, honestly graded, and producing a concrete artifact. 56 frameworks + 4 tools + 9 recipes for Claude Code, Codex, and other AI agents. Advanced (Gold) tier.

Install
npx -y skills add product-on-purpose/thinking-framework-skills --skill think-red-team-light

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Produces an adversarial critique by constructing the strongest case against a proposal or thesis (the best objections an intelligent adversary would raise), then judging which objections actually land and what would rebut them. Use when a plan has too-easy consensus and needs pressure-testing, or to steelman the opposition before committing.

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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<!-- thinking-framework-skills | https://github.com/product-on-purpose/thinking-framework-skills | Apache-2.0 -->

Red Team Light

Plans that reach easy consensus go untested. This skill suspends the cooperative stance and constructs the strongest case against a single proposal or thesis: the best objections a motivated, intelligent adversary would raise (steelman, not strawman), then judges which land and what would rebut them. The output is an adversarial critique. Honest limit: an AI red team is constructed, role-played dissent, and role-played dissent does not match genuine dissent (Nemeth) - so for high stakes it flags whether a real dissenting view should be sought, not just the model's.

When to Use

  • A plan has too-easy consensus and nobody is really arguing the other side.
  • Before committing to a strong thesis or recommendation.
  • To pressure-test the agent's own confident output.

When NOT to Use

  • When the team needs alignment and buy-in more than another critique.
  • When you need failure causes over time (use premortem) or a rounded multi-lens view (use parallel perspectives).
  • If it would only produce performative contrarianism rather than the strongest objections.

Instructions

When asked to red team, follow these steps:

  1. State the thesis fairly in one or two sentences - the proposal being attacked, in its strongest honest form.
  2. Build the strongest objections. Adopt a genuinely adversarial stance and construct the best case against it: where it is weakest, what an informed critic or competitor would attack, what evidence cuts against it. Steelman, do not strawman.
  3. Rank by force. Order the objections by how much damage they do if true, not by how easy they are to raise.
  4. Test each. For the top objections, state how the thesis would have to answer them, and whether it plausibly can.
  5. Verdict. Say which objections are decisive (would sink or substantially change the plan) and which are survivable. For high stakes, note whether a real, independent dissenting view should be sought, given this is constructed dissent.
  6. Emit the critique per references/TEMPLATE.md.

Output Format

Use the template in references/TEMPLATE.md. The deliverable is the ranked objections with verdicts, not prose.

Quality Checklist

Before finalizing, verify:

  • Objections are steelmanned (strongest form), not strawmen.
  • They are ranked by force, not by ease.
  • Each top objection has how the thesis must answer it.
  • The verdict names which objections are decisive.
  • It notes whether genuine (not constructed) dissent should be sought for high stakes.
  • The output is the adversarial critique artifact, not prose.

Evidence

Tier P (flagged). Adversarial review (red teaming, from military/intelligence/security practice) surfaces objections cooperative review misses. But Nemeth et al. (2001) found role-played dissent does not replicate the reasoning gains of authentic dissent, and an AI red team is constructed dissent, so it is a blind-spot finder, not a substitute for a real dissenter. Evidence is transferred from human contexts, not AI-validated. Full grading: evidence/dossier.md.

Examples

See references/EXAMPLE.md for a completed critique.

What ships with it: 5 files

15.8 KB alongside SKILL.md

eval/

evidence/

references/

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