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 Ootto-AI/claude-content-skills --skill profile-conversion-auditgit clone --depth 1 https://github.com/Ootto-AI/claude-content-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/ootto-ai/claude-content-skills/profile-conversion-audit)<a href="https://agentmods.dev/skills/ootto-ai/claude-content-skills/profile-conversion-audit"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/profile-conversion-audit/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/ootto-ai/claude-content-skills/profile-conversion-audit"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/profile-conversion-audit.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 | $0.00127 | $0.00657 |
| Opus 5 | $0.00063 | $0.00329 |
| Sonnet 5 | $0.00025 | $0.00131 |
| Haiku 4.5 | $0.00013 | $0.00066 |
Grade A, and why
profile-conversion-audit 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile Conversion Audit
Review the profile as a visitor journey: immediate understanding, credible evidence, useful navigation, and one truthful next step.
1. Capture the profile as a visitor sees it
Ask for the profile URL or supplied screenshots, platform, audience context, current objective, linked destination, and constraints. Review the visible name, category, bio, links, pinned material, highlights or featured items, recent posts, and contact route only as they actually appear.
2. Test the first-ten-seconds questions
Can the right visitor tell who the account helps, what it helps with, why it is credible, and what to do next? Record missing information, competing actions, jargon, unsupported claims, inaccessible media, and mismatches between the profile and linked destination.
3. Recommend evidence-backed changes
Prioritise changes by clarity and risk: identity, audience situation, approved promise, proof, navigation, and action. Supply proposed copy only from approved facts and proof. Explain why each change addresses a visitor question and what must remain unchanged for disclosure, brand, or platform policy.
4. Define a reversible validation plan
State what can be changed by the profile owner, what needs approval, and how to observe the result using the data actually available. Change one meaningful element at a time where possible. Treat outcomes as evidence for the next iteration, not a promised uplift.
Hard rules
- Do not invent follower counts, customer logos, results, features, availability, or verification status.
- Never promise a conversion-rate improvement from a profile edit.
- Keep all claims aligned with the approved landing destination and product reality.
- Do not recommend deceptive urgency, misleading links, or hidden disclosures.
- Respect platform constraints and accessibility for text, captions, images, and contact routes.
Failure modes
| Failure | Do this instead |
|---|---|
| The audit optimises the bio alone | Review the full visitor path: profile, proof, featured material, and destination. |
| A profile says everything to everyone | Choose the approved primary audience situation and one clear action. |
| Proof is added without permission | Use social-proof-mining and publish only cleared evidence. |
| Multiple changes hide what improved | Prioritise and validate one meaningful change at a time. |
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 · 46 lines · 127 tokens per session scan A c2ffb5eecd6b
profile-conversion-audit is a skill published in the GitHub repository Ootto-AI/claude-content-skills (28 stars, last pushed 19d ago), licensed MIT. It adds 127 tokens to every session and 657 once invoked, about $0.0006 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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