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-ethics-consent-reviewgit 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-ethics-consent-review)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-ethics-consent-review"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-ethics-consent-review/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-ethics-consent-review"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-ethics-consent-review.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 | $0.00120 | $0.01504 |
| Opus 5.5 | $0.00048 | $0.00602 |
| Sonnet 5.5 | $0.00024 | $0.00301 |
| Haiku 4.5 | $0.00012 | $0.00150 |
Grade A, and why
s4h-ethics-consent-review 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 1mo 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ethics Consent Review
Consent is not a checkbox. It is a meaningful act by a person who understands what they're agreeing to, genuinely has the option to decline, and isn't being manipulated into compliance.
Most consent failures aren't malicious — they're the accumulated result of copy-paste terms, optimised conversion flows, and defaults set by people who never questioned them. This review surfaces those failures before they become patterns users resent or regulators flag.
The Three Tests
Every consent decision must pass three tests:
Informed — Does the person genuinely understand what they're agreeing to? Not technically (buried in ToS), but practically. If you explained it plainly in conversation, would they be surprised?
Voluntary — Does the person genuinely have the ability to decline? Is declining as easy as accepting? Are there consequences for declining that make the choice effectively coerced?
Meaningful — Does the person's choice actually matter? Is there genuine optionality, or is the "choice" cosmetic — the default is set to the outcome the business wants and the friction to change it is high?
Your Process
Step 1: Map the consent moment What specifically is the user being asked to consent to? When in the flow does this happen? What is the default? What happens if they decline?
Framing check: Confirm the ethical situation and the parties affected before continuing. State what you've identified — the specific consent moment, the UX or data practice under review, and who is giving consent — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the specific consent moment and context]. 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.
- 1mo ago First seen · 128 lines · 120 tokens per session scan A 1c825cd83a28
s4h-ethics-consent-review is a skill published in the GitHub repository human-avatar/skills-for-humanity (236 stars, last pushed 3mo ago), licensed MIT. It adds 120 tokens to every session and 1,504 once invoked, about $0.0005 per session on Opus 5.5. 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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