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.
npx skills add deciqAI/knowledge-skills --skill six-thinking-hatsgit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote 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.
[](https://agentmods.dev/skills/deciqai/knowledge-skills/six-thinking-hats)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/six-thinking-hats"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/six-thinking-hats/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.
<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/six-thinking-hats"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/six-thinking-hats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.02182 |
| Opus 5 | $0.00049 | $0.01091 |
| Sonnet 5 | $0.00020 | $0.00436 |
| Haiku 4.5 | $0.00010 | $0.00218 |
Grade A, and why
six-thinking-hats 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Six Thinking Hats
Overview
Six Thinking Hats (Edward de Bono, 1985) prevents the most common meeting failure: different thinking modes colliding simultaneously. The fix is parallel thinking — everyone uses the same mode at the same time. Six hats: White (data/facts), Red (gut/emotions), Black (caution/risk), Yellow (optimism/value), Green (creativity/alternatives), Blue (process/meta).
ABB CEO Percy Barnevik cut 12-hour cross-cultural management meetings to under 2 hours after adoption. IBM and DuPont embedded the method in leadership development.
Compose with neighbors: lateral-thinking populates Green Hat. critical-thinking runs inside Black Hat. mece structures the White Hat data phase.
When to Use
Use when: group decision degenerates into debate; proposal needs multi-angle evaluation; creative ideas get killed by habitual criticism; someone says "let's look at this from all angles," "we keep going in circles," "we need structure"; individual high-stakes decision needs forced multi-angle review; a platform-shift bet needs balanced evaluation (e.g. "should we go all-in on AI agents / AI-native," "is our AI capex justified," "how do we weigh AI adoption risk vs. AI-native competition").
When NOT: deep specialist analysis required (use hats for framing only); group too political (hat roles used as cover); time under 10 minutes; question is purely factual (run critical-thinking).
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a specific decision ready → run The Process directly.
- Coach mode: user is unfamiliar or has no concrete case → guide step by step. In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line what-it-is. Six Thinking Hats separates discussion into six modes so everyone explores each angle together instead of arguing from different angles simultaneously.
- Check fit — if the group is too political, question is purely factual, or time is under 10 minutes, redirect or modify.
- Elicit the specific decision or proposal. "We need better meetings" is not workable; "should we launch feature X in Q3 or delay to Q4" is.
[WAIT — do not advance until user responds]
- One hat at a time. Walk through each hat in sequence, posing the hat's key question and waiting for input before moving to the next.
[WAIT — do not advance until user responds]
- Close by naming which hat revealed the most unexpected insight — the angle the team would have missed in an unstructured discussion.
[WAIT — do not advance until user responds]
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 125 lines · 98 tokens per session scan A af85277948e4
six-thinking-hats is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 11d ago), licensed MIT. It adds 98 tokens to every session and 2,182 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
cro
Conversion audit for funnels and pages — a section-by-section friction log (clarity, anxiety, distraction, motivation), heuristic checks (message match, above-the-fold value prop, form cost), an ICE-scored hypothesis backlog, and top-3 A/B test designs with success metrics and minimum-sample notes. Use when the user…
prompt-master
Generates optimized prompts for AI tools. Activates only when the user explicitly asks to write, fix, improve, or adapt a prompt for a specific AI tool (LLM, Cursor, Midjourney, image AI, video AI, coding agents, etc.). Does not activate for general conversation, coding tasks, document writing, or other…
slack-tools
Slack workspace management and automation specialist.
syndic
Gère un parc de copropriétés en France avec vue portfolio consolidée. Couvre administration, comptabilité (décret 2005, plan comptable copro, 5 annexes), assemblées générales (convocation, PV, notification), appels de fonds, travaux, fournisseurs, recouvrement d'impayés et transition de syndic. Maîtrise les majorités…
ops-suggest
Show time-aware CocoOps operational suggestions from the deterministic ops-suggest classifier. Usage: $ops suggest.
customer-onboarding-and-implementation
Takes a new customer from signature to working — setting a definition of live that both sides agreed before the contract was signed, planning and staffing the implementation, running data migration and integration realistically, training the people who will actually use it, and handing over to the ongoing…