decision-bias-check

decision-bias-check is a skill for Claude Code from cdeust/zetetic-team-subagents. It costs 67 tokens per session (706 once invoked), scanned A, original, MIT.

A guide for checking decisions and plans for bias, weak evidence, hidden downside and failure under unusual conditions.

In plain words
What is it for?
Use it for high-stakes choices, estimates, negotiations, strategy, metric design, pre-mortems and plans that need clear evidence or small tests.
Why use it?
It adds an adversarial review before commitment, including tests for unfalsifiable claims, optimistic estimates and metrics that no longer measure their intended goal.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the zetetic-team-subagents plugin — 16 skills, 2 commands, 23 agents, 7 hooks, 1 MCP server shipped together

Good fit Use it for high-stakes choices, estimates, negotiations, strategy, metric design, pre-mortems and plans that need clear evidence or small tests.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cdeust/zetetic-team-subagents/decision-bias-check
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add cdeust/zetetic-team-subagents --skill decision-bias-check
Clone the repo
git clone --depth 1 https://github.com/cdeust/zetetic-team-subagents

Made for: Claude Code.

Or install zetetic-team-subagents, the plugin that ships this one along with the rest of its 16 skills, 2 commands, 23 agents, 7 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for decision-bias-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/decision-bias-check/github.svg)](https://agentmods.dev/skills/cdeust/zetetic-team-subagents/decision-bias-check)
Your own site
<a href="https://agentmods.dev/skills/cdeust/zetetic-team-subagents/decision-bias-check"><img src="https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/decision-bias-check/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for decision-bias-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/cdeust/zetetic-team-subagents/decision-bias-check"><img src="https://agentmods.dev/badge/skills/cdeust/zetetic-team-subagents/decision-bias-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 706 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.00706
Opus 5 $0.00034 $0.00353
Sonnet 5 $0.00013 $0.00141
Haiku 4.5 $0.00007 $0.00071

Measured 11d ago against content hash 9fa8cd9270cf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

decision-bias-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/decision-bias-check/SKILL.md · 50 lines

How it starts

The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Decision Bias Check

Problem shape: a decision, plan, or evaluation is about to be committed and nobody has run the adversarial pass: which bias produced it, what would refute it, how it behaves in the tails, and whether the metric still measures what it was meant to.

Relevant geniuses

Agent Use when
kahneman fast intuition on a high-stakes call; no pre-mortem; estimate needs a reference class; an easier question was answered instead of the hard one
taleb exposure to volatility unclassified (fragile/robust/antifragile); improvement always by addition; decision-makers carry no downside
popper claim has no observation that could refute it; only easy confirmations offered as evidence; plan too big to test piecemeal
simon optimizing where satisficing is rational; the search space needs decomposing before choosing
boyd adversarial setting — the other side adapts; tempo and orientation matter more than the single best move
zhuangzi the metric has become the target (Goodhart); the evaluation framework itself needs auditing
ibnalhaytham an authority's claim taken on trust — systematic doubt with controlled isolation of variables
rogerfisher multi-stakeholder deadlock — separate interests from positions, find the BATNA and the zone of agreement

Invocation

  1. Pick the best-fit agent above. If two or more fit, run tools/genius-invoker.sh route "<problem>" and take the top ranked match.
  2. Load it: tools/genius-invoker.sh invoke <agent> "<problem>", then read agents/genius/<agent>.md in full.
  3. Apply the agent's <workflow> step by step and answer in its <output-format>. The output names the specific bias/failure with its evidence — not a generic "consider other perspectives".
  4. Typical chain: kahneman audits the intuition → popper designs the severe test → taleb classifies the tail exposure. Run via tools/genius-invoker.sh compose kahneman popper -- "<problem>".
  5. If no shape above matches, use a standard team agent instead.

Read the full file on GitHub · 50 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 50 lines · 67 tokens per session scan A 9fa8cd9270cf

Subscribe to this mod's changes

decision-bias-check is a skill published in the GitHub repository cdeust/zetetic-team-subagents (7 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 706 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories