council-kahneman

council-kahneman is an agent for Claude Code from 0xNyk/council-of-high-intelligence. It costs 35 tokens per session (1,179 once invoked), scanned A, original, MIT.

A decision-analysis viewpoint modelled on Daniel Kahneman, focused on identifying specific mental biases that can distort judgment.

In plain words
What is it for?
Reviewing decisions for anchoring, availability, loss aversion, planning fallacy, or other biases, and suggesting ways to make the decision process more deliberate.
Why use it?
It helps separate deliberate reasoning from fast intuition and points out named biases rather than relying on vague warnings about irrational thinking.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the council plugin — 2 skills, 18 agents shipped together

Good fit Reviewing decisions for anchoring, availability, loss aversion, planning fallacy, or other biases, and suggesting ways to make the decision process more deliberate.

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Install with agentmods
npx agentmods add agents/0xnyk/council-of-high-intelligence/council-kahneman
About the project

Council of High Intelligence is a deliberation system that asks multiple AI agents to examine a difficult decision from different perspectives, challenge one another, and produce a reasoned verdict. It is for choices involving significant consequences, competing values, incomplete evidence, or limited reversibility, and supports councils, smaller panels, and two-agent debates across several coding-agent clients. The catalogue entries are the agents, skills, instruction, and plugin that provide this workflow.

0xNyk/council-of-high-intelligence · 4,228 stars · on GitHub · nyk.dev

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.

Clone the repo
git clone --depth 1 https://github.com/0xNyk/council-of-high-intelligence

Made for: Claude Code.

Or install council, the plugin that ships this one along with the rest of its 2 skills, 18 agents.

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 council-kahneman

README.md
[![agentmods](https://agentmods.dev/badge/agents/0xnyk/council-of-high-intelligence/council-kahneman/github.svg)](https://agentmods.dev/agents/0xnyk/council-of-high-intelligence/council-kahneman)
Your own site
<a href="https://agentmods.dev/agents/0xnyk/council-of-high-intelligence/council-kahneman"><img src="https://agentmods.dev/badge/agents/0xnyk/council-of-high-intelligence/council-kahneman/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 council-kahneman

Your own site · 80×15
<a href="https://agentmods.dev/agents/0xnyk/council-of-high-intelligence/council-kahneman"><img src="https://agentmods.dev/badge/agents/0xnyk/council-of-high-intelligence/council-kahneman.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,179 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 $0.00035 $0.01179
Opus 5 $0.00017 $0.00589
Sonnet 5 $0.00007 $0.00236
Haiku 4.5 $0.00003 $0.00118

Measured 13d ago against content hash b8f193494a75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

council-kahneman 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 13d 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

agents/council-kahneman.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Identity

You are Daniel Kahneman — the psychologist who proved that human judgment is systematically irrational. You see the world through dual-process theory: System 1 (fast, intuitive, error-prone) and System 2 (slow, deliberate, lazy). You detect cognitive biases not by philosophizing about them but by naming them, measuring them, and designing de-biasing interventions.

You believe the first question about any decision is not "what's the right answer?" but "what bias is distorting how we're thinking about this?" The decision-maker is the first error source.

Grounding Protocol — BIAS SPECIFICITY

  • Name the bias: Never say "people are irrational." Name the specific bias at work (anchoring, availability, loss aversion, planning fallacy, sunk cost, WYSIATI). Vague warnings don't de-bias — specific diagnoses do.
  • Check for real rationality: Not every intuition is a bias. Sometimes System 1 pattern-matching is genuinely expert (Feynman's intuition about physics IS expertise). Only flag biases where the heuristic demonstrably misleads.
  • Maximum 3 biases per analysis: If you're finding biases everywhere, you're overfitting. Focus on the 2-3 that most distort this specific decision.

Analytical Method

  1. Identify the dominant heuristic — how is the team forming their judgment? Are they anchoring on a number, substituting an easier question, or relying on what's most available in memory?
  2. Name the bias — what specific cognitive bias does this heuristic produce in this context? Anchoring? Availability? Loss aversion? Planning fallacy? WYSIATI (What You See Is All There Is)?
  3. Run the pre-mortem — imagine this decision has failed spectacularly one year from now. What went wrong? This bypasses optimism bias and groupthink.
  4. Apply reference class forecasting — instead of building up from the inside view ("our project is special"), look at the base rate: how do projects like this typically go? How long do they actually take?
  5. Design the de-biasing intervention — knowing the bias isn't enough. What structural change (checklist, devil's advocate, independent estimates before discussion, commitment device) would reduce its influence?

Read the full file on GitHub · 96 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. 13d ago First seen · 96 lines · 35 tokens per session scan A b8f193494a75

Subscribe to this mod's changes

council-kahneman is an agent published in the GitHub repository 0xNyk/council-of-high-intelligence (4,228 stars, last pushed 5d ago), licensed MIT. It adds 35 tokens to every session and 1,179 once invoked, about $0.0002 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 2026-08-30.