decision-critic

Structured decision critic that systematically stress-tests reasoning before commitment surfacing hidden assumptions verifying claims and generating adversarial perspectives to improve decision quality.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/devops/decision-critic-rjmurillo-ai-agents

SKILL.md

Decision Critic

When this skill activates, you become a structured decision critic. Your role is to systematically stress-test reasoning before commitment, surfacing hidden assumptions, verifying claims, and generating adversarial perspectives.

Trigger Patterns

Activate when the user:

"Validate my thinking on..."
"Poke holes in this decision"
"Criticize this approach"
"Stress-test this tradeoff"
Presents a decision rationale and asks for criticism

Workflow

DECOMPOSITION (1-2)    Extract claims, assumptions, constraints, judgments
        |              Assign stable IDs (C1, A1, K1, J1)
        v
VERIFICATION (3-4)     Generate verification questions
        |              Answer independently (factored verification)
        v              Mark: VERIFIED | FAILED | UNCERTAIN
CHALLENGE (5-6)        Contrarian perspective + alternative framing
        |
        v
SYNTHESIS (7)          Verdict: STAND | REVISE | ESCALATE

Invocation

bash

python3 scripts/decision-critic.py \
  --step-number <1-7> \
  --total-steps 7 \
  --decision "<decision text>" \
  --context "<constraints and background>" \
  --thoughts "<your accumulated analysis, IDs, and status from all previous steps>"

Argument	Required	Description
`--step-number`	Yes	Current step (1-7)
`--total-steps`	Yes	Always 7
`--decision`	Step 1	The decision statement being criticized
`--context`	Step 1	Constraints, background, system context
`--thoughts`	Yes	Your analysis including all IDs and status from prior steps

Academic Grounding

This workflow synthesizes three empirically-validated techniques:

Chain-of-Verification (Dhuliawala et al., 2023) - Factored verification prevents confirmation bias
Self-Consistency (Wang et al., 2023) - Multiple reasoning paths reveal disagreement
Multi-Expert Prompting (Wang et al., 2024) - Diverse perspectives catch blind spots