cognitive-bias-detector
SkillDocs & knowledgeAudits design documents, sprint estimates, and technical debates for cognitive biases like anchoring, sunk cost, and optimistic scoping.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the cognitive-bias-detector skill
What this skill tells your AI
The instructions your AI receives, as published by codebygarv/ai-skills in skills/reasoning/cognitive-bias-detector/SKILL.md and read by ahel’s review.
Purpose
Detect and correct human cognitive distortions in engineering planning, architectural choices, and project roadmaps to avoid predictable traps.
When to Use
- Reviewing sprint estimates or project milestone plans.
- When a team insists on maintaining an obsolete custom system (sunk cost).
- When a design heavily mirrors the author's previous company stack (availability bias / law of the instrument).
What to Analyze
- Sunk Cost Fallacy: Continuing an unviable strategy because of prior invested hours.
- Planning Fallacy & Optimism Bias: Assuming perfect zero-defect execution with no buffer.
- Law of the Instrument (Maslow's Hammer): Forcing a familiar tool onto a mismatched problem.
- Anchoring: Sticking to an initial off-the-cuff estimate or early architectural idea.
- Confirmation Bias: Highlighting only benchmarks that flatter the preferred tool.
Output Format
- Identified Biases: Name, trigger quote/claim, and underlying fallacy.
- Risk Assessment: How this bias distorts delivery date, stability, or budget.
- Corrective Re-framing: Unbiased re-evaluation questions.
Avoid
- Accusatory or personal attacks.
- Dismissing valid domain experience as bias.
Signals
- GitHub stars
- 25
- Forks
- 1
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
cognitive-bias-detector- Source
- github.com/codebygarv/ai-skills