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 human-avatar/skills-for-humanity --skill s4h-creativity-concept-fangit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-creativity-concept-fan)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-creativity-concept-fan"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-creativity-concept-fan/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/human-avatar/skills-for-humanity/s4h-creativity-concept-fan"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-creativity-concept-fan.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 | $0.00081 | $0.01483 |
| Opus 5 | $0.00041 | $0.00741 |
| Sonnet 5 | $0.00016 | $0.00297 |
| Haiku 4.5 | $0.00008 | $0.00148 |
Grade A, and why
s4h-creativity-concept-fan 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.
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.
You are facilitating a Concept Fan session using Edward de Bono's technique. The Concept Fan is a tool for expanding solution space — it prevents premature commitment to one approach by making the full landscape of alternatives visible first.
Why the concept fan matters
Most thinking about solutions is too narrow. We take a goal, think of one or two approaches, evaluate them, and pick the best. This feels thorough but it's actually a small sample of the possible solution space.
The Concept Fan works by moving up and down a ladder of abstraction. At the top is the broadest possible framing of what you're trying to achieve — the pure purpose. At the bottom are specific implementations. Between them are concepts — general approaches that can each spawn multiple implementations.
By mapping this landscape before committing, you avoid the trap of evaluating implementations when you should still be choosing concepts.
The structure
Think of a fan with a handle and radiating spokes:
- The handle is the goal — what you're ultimately trying to achieve, stated at its broadest useful level
- First ring of spokes are broad concepts — different general approaches to achieving the goal
- Second ring of spokes are sub-concepts — more specific approaches within each broad concept
- Outer ring are specific implementations — concrete things you could actually do
The fan expands outward from abstract to specific. At each level, the question is: "What are all the different ways to achieve this?"
Your process
Step 1: Establish the goal State the user's goal at two levels:
- Immediate goal: what they said they want
- Purpose level: why they want it — the underlying need it serves
The purpose level is important because it sometimes reveals entirely different solution families that address the real need without solving the stated problem.
Framing check: Confirm the specific challenge before continuing. State what you've identified — the actual goal being pursued and the purpose level behind it — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the goal and its underlying purpose]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different situation than read; incorporate the correction before proceeding
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.
- 13d ago First seen · 125 lines · 81 tokens per session scan A d88e08858d51
s4h-creativity-concept-fan is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 1,483 once invoked, about $0.0004 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.
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