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Agora Doubt List

Generate a Cartesian verification artifact before trusting a plan, claim, implementation, or release. Turn confidence into explicit checks.
Generate a Cartesian verification artifact before trusting a plan, claim, implementation, or release. Turn confidence into explicit checks.
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未分类 clawhub v2.2.0 1 版本 100000 Key: 无需
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概述

Doubt List

Purpose

Convert confidence into verifiable skepticism.

This skill asks: what must be checked before we trust this?

It is not for performative negativity. It exists to separate fact, inference, preference, and guess.

Activate when

Use this skill when:

  • a plan sounds persuasive but has not been stress-tested
  • a release is nearing shipment
  • a claim is important, risky, or governance-sensitive
  • the team wants a verification checklist before execution
  • consequences of error are high

Inputs

Expected inputs may include:

  • a feature or release plan
  • a design proposal
  • a decision memo
  • a claim or assertion set
  • implementation notes or test results

Classification rule

Before generating doubts, classify each major statement as one of:

  • Fact — directly established or evidenced
  • Inference — reasoned from available evidence
  • Preference — normative or taste-based judgment
  • Guess — plausible but currently unverified

Unclassified claims are not ready for trust.

Doubt categories

Always produce doubts across five categories.

1. Happy path doubts

  • What must go right for the main story to hold?
  • Which "obvious" success condition has not actually been verified?

2. Edge case doubts

  • What happens under uncommon but realistic conditions?
  • What retries, partial failures, or weird inputs have been ignored?

3. Boundary doubts

  • What breaks at minimum, maximum, empty, overloaded, concurrent, or delayed conditions?

4. Ambiguity doubts

  • Which terms or promises could be interpreted in more than one way?
  • Which claims sound specific but are not operationally defined?

5. Evil demon scenarios

  • What if the most confidence-inducing assumption is false?
  • What if the evidence is incomplete, stale, biased, or misread?
  • What catastrophic but low-frequency scenario would embarrass the team later?

Procedure

Step 1 — State the object of doubt

Name exactly what is being reviewed.

Step 2 — Classify key claims

Mark each important claim as Fact / Inference / Preference / Guess.

Step 3 — Generate doubts across all five categories

Do not stop at happy path concerns.

Step 4 — Convert doubts into checks

Every serious doubt should map to a concrete verification action.

Step 5 — Assign release posture

Conclude whether the work is:

  • Clear enough to proceed
  • Proceed with conditions
  • Do not proceed yet

Output artifact

## Doubt List

### Object of Review
- ...

### Claim Classification
- Claim: ... -> Fact / Inference / Preference / Guess

### Happy Path Doubts
- Doubt: ...
- Verification: ...

### Edge Case Doubts
- Doubt: ...
- Verification: ...

### Boundary Doubts
- Doubt: ...
- Verification: ...

### Ambiguity Doubts
- Doubt: ...
- Verification: ...

### Evil Demon Scenarios
- Doubt: ...
- Verification: ...

### Clarity Gate
- Clear: ...
- Not clear: ...

### Release Posture
- Proceed / Proceed with conditions / Do not proceed yet

Guardrails

  • Do not confuse disagreement with evidence.
  • Do not mark a guess as fact because the team likes it.
  • Do not stop at implementation QA; plans, memos, and claims also need doubt.
  • Do not generate abstract doubts without corresponding verification actions.

Failure modes

Common failure modes:

  • only checking the happy path
  • writing doubts that are too vague to test
  • skipping claim classification
  • treating rhetorical confidence as evidence
  • using this skill to block progress without naming concrete conditions for trust

Escalation points

Escalate when:

  • the key claim cannot be verified with currently available evidence
  • the team is relying on guesswork for a high-consequence decision
  • release pressure is overriding clarity
  • terms in the proposal are too ambiguous for meaningful review

Completion condition

This skill is complete only when a reviewer could pick up the output and know what to verify next.

版本历史

共 1 个版本

  • v2.2.0 当前
    2026-05-07 17:34 安全 安全

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