huddle

A structured way to examine a difficult decision through several viewpoints, based on Six Thinking Hats: facts, feelings, risks, benefits, and new ideas. It can use one or more professional perspectives and produces structured findings for review.

In plain words
What is it for?
Use it for `/huddle` requests involving decisions, debates, architecture reviews, or red-team and blue-team analysis.
Why use it?
It reduces the chance that a decision is judged from only one angle by separating evidence, concerns, advantages, and alternatives. The structured findings make different viewpoints easier to compare.

Skill for Claude CodeCodex

Part of the ai-native-toolkit plugin — 15 skills, 7 commands, 8 agents shipped together

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.

agentmods
npx agentmods add skills/bjcoombs/ai-native-toolkit/huddle
Any agent
npx skills add bjcoombs/ai-native-toolkit --skill huddle
Clone the repo
git clone --depth 1 https://github.com/bjcoombs/ai-native-toolkit

Made for: Claude Code, Codex.

Or install ai-native-toolkit, the plugin that ships this one along with the rest of its 15 skills, 7 commands, 8 agents.

Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,834 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
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 $0.00092 $0.08834
Opus 5 $0.00046 $0.04417
Sonnet 5 $0.00018 $0.01767
Haiku 4.5 $0.00009 $0.00883

Measured 3d ago against content hash d1903e36ea40, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

huddle scanned grade C with 1 finding 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 3d 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.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

<!-- chat-replace:phased-spawn-instructions -->
skills/huddle/SKILL.md · 520 lines

How it starts

The opening of the file, as written. The whole thing — 520 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Huddle - Six Thinking Hats Analysis

Scales from a solo gut check to a board-level deliberation using Fibonacci team sizing.

Architecture

You are Blue Hat - the chair. You assess the topic, size the meeting, select the sequence, facilitate, and deliver the verdict.

Hat agents (white-hat, red-hat, black-hat, yellow-hat, green-hat) are methodology specialists in ~/.claude/agents/, dispatched via the Agent tool with subagent_type=<hat>.

Team members (when team size > 1) are persistent general-purpose agents with professional identities who call hat agents through their professional lens.

Hat Findings Schema

Every hat agent returns its findings as one structured object - the unit the chair synthesises, the critic reviews, and the discovery loop tests for new claims. It is the same shape in all three execution modes (solo, phased, team).

{
  "lens": "",
  "hat": "white|red|black|yellow|green",
  "claims": [
    { "claim": "", "severity_or_value": "HIGH|MEDIUM|LOW | positive | neutral", "evidence": "" }
  ]
}
  • lens - the professional lens the finding came through (e.g. security-eng); empty/blue for solo, where the chair runs the hats directly.
  • severity_or_value - reads by hat: Black uses risk severity (HIGH/MEDIUM/LOW); Yellow/Green use opportunity value (positive/neutral); White facts carry no severity (neutral); Red records the gut-check signal in the same field (e.g. HIGH unease, positive pull).
  • evidence - the file, quote, datum, or reasoning the claim rests on. An empty evidence is what the completeness-critic flags as an unverified claim.

Capability Requirements

Three execution modes exist. Pick one deterministically: team size = 1 → solo flat-parallel; team size ≥ 2 AND you can confirm the team-mode capability (SendMessage plus background Agent teammates) is available → team mode; otherwise → phased sub-agent mode. Confirming availability means actively probing, not glancing at your visible tools - SendMessage may be deferred behind ToolSearch (see the capability-detection step). If, after probing, you still cannot reach team mode, default to phased - it degrades gracefully, whereas attempting team mode without the capability fails loudly.

Read the full file on GitHub · 520 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. 3d ago First seen · 520 lines · 92 tokens per session scan C d1903e36ea40

Subscribe to this mod's changes

huddle is a skill published in the GitHub repository bjcoombs/ai-native-toolkit (30 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 92 tokens to every session and 8,834 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.