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 Owl-Listener/ai-design-skills --skill consent-and-agencygit clone --depth 1 https://github.com/Owl-Listener/ai-design-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/owl-listener/ai-design-skills/consent-and-agency)<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/consent-and-agency"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/consent-and-agency/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/owl-listener/ai-design-skills/consent-and-agency"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/consent-and-agency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00020 | $0.00513 |
| Opus 5 | $0.00010 | $0.00257 |
| Sonnet 5 | $0.00004 | $0.00103 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
consent-and-agency 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 12d 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consent and Agency
AI products make decisions, take actions, and process information on behalf of users. Consent and agency design ensures users remain in control — understanding what the AI does, agreeing to it, and being able to override it.
Informed Consent for AI
Users should understand and agree to:
- What data the AI uses: Conversation history, personal data, uploaded documents, browsing behaviour
- What the AI does with it: Training, personalisation, sharing with third parties, storage
- What actions the AI takes: Sending messages, making changes, accessing systems
- What the AI can't do: Limitations that might affect the user's expectations Consent is not a checkbox at sign-up. It's an ongoing design challenge throughout the experience.
Designing for Agency
Agency means the user feels — and is — in control:
- Opt-in over opt-out: AI features should be activated by the user, not imposed
- Reversibility: AI actions should be undoable wherever possible
- Override mechanisms: The user can always stop, redirect, or override the AI
- Exit paths: The user can disengage from AI assistance at any point without penalty
- Preference controls: The user can adjust AI behaviour, scope, and autonomy levels
Consent Patterns
- Progressive consent: Ask for permission incrementally as new capabilities are needed, not all at once
- Contextual consent: Ask at the moment the action is about to happen, not in advance
- Granular consent: Let users consent to specific actions or data uses, not blanket permissions
- Revocable consent: Users can withdraw consent and have that withdrawal take effect
Agency Anti-Patterns
- Dark patterns: Making it hard to opt out or override the AI
- Consent fatigue: Asking for permission so often that users click through without reading
- Learned helplessness: AI does so much that users forget how to do things themselves
- Invisible actions: The AI takes actions the user doesn't know about
- Irreversible defaults: AI actions that can't be undone without user awareness
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.
- 12d ago First seen · 38 lines · 20 tokens per session scan A bb8f0c9dbe0e
consent-and-agency is a skill published in the GitHub repository Owl-Listener/ai-design-skills (173 stars, last pushed 3mo ago), licensed MIT. It adds 20 tokens to every session and 513 once invoked, about $0.0001 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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