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-identity-values-clarificationgit 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-identity-values-clarification)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-identity-values-clarification"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-identity-values-clarification/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-identity-values-clarification"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-identity-values-clarification.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 | $0.00068 | $0.01005 |
| Opus 5 | $0.00034 | $0.00502 |
| Sonnet 5 | $0.00014 | $0.00201 |
| Haiku 4.5 | $0.00007 | $0.00101 |
Grade A, and why
s4h-identity-values-clarification 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Values Clarification
Stated values are aspirational. Operative values are revealed by decisions under pressure — especially when values conflict with cost, convenience, or competing interests. The gap between stated and operative values is where integrity problems live, and where the most useful clarification work happens.
Your Process
Step 1: State the Values Being Invoked Not abstract words — translate each value into a behavioural definition. "What does this value mean in practice? What behaviour does it require, and what behaviour does it prohibit?"
- Instead of: "We value innovation."
- Write: "We value innovation — meaning we fund experiments that might fail and do not punish people for thoughtful bets that don't pay off."
Framing check: Confirm the specific subject before continuing. State what you've identified — the entity whose values are being examined and the set of stated values in scope — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the entity and the values under examination]. 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
Step 2: Find Recent Decisions That Confirmed Each Value For each value: what recent decision or action was consistent with the behavioural definition? Be specific — name the decision.
Step 3: Find Recent Decisions That Contradicted Each Value For each value: what recent decision or action contradicted the behavioural definition? These are the most diagnostic data points.
Step 4: Identify Where Values Conflicted Where did two values pull in opposite directions? When values conflict, one wins. The outcome reveals which value actually takes priority — the real priority order, not the stated one.
Step 5: State the Operative Values Based on the evidence from Steps 2–4: what are the actual, operative values — as demonstrated by behaviour? Where do they differ from stated values?
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 · 92 lines · 68 tokens per session scan A 89c0084248f4
s4h-identity-values-clarification is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 1,005 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 2026-09-03.
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