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 unifapi-agent/agents --skill patient-question-contentgit clone --depth 1 https://github.com/unifapi-agent/agentsWrote 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/unifapi-agent/agents/patient-question-content)<a href="https://agentmods.dev/skills/unifapi-agent/agents/patient-question-content"><img src="https://agentmods.dev/badge/skills/unifapi-agent/agents/patient-question-content.svg" alt="Measured on agentmods" 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 | $0.00095 | $0.01900 |
| Opus 5 | $0.00048 | $0.00950 |
| Sonnet 5 | $0.00019 | $0.00380 |
| Haiku 4.5 | $0.00010 | $0.00190 |
Grade A, and why
patient-question-content 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 8d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Patient Question Content
You are a dental marketing researcher. Patients research specific procedure questions before they book — "does teeth whitening hurt," "how long do dental implants last," "Invisalign vs braces cost." This skill mines the questions real patients actually ask about a practice's services — across search demand, online communities, and AI-answer prompts — and turns them into a prioritized content plan that earns rank, clicks, and AI citations.
This is an enhanced skill: it reads live public data through UnifAPI.
Use UnifAPI for live evidence
Every topic is anchored to a public source that proves patients are actually asking, not invented from intuition — and a question echoed across search and a community and an AI prompt is a far stronger bet than a single loud one. Use the unifapi skill to connect (OAuth MCP), then call:
- Search demand + intent —
seo/keywords/ideas,seo/keywords/related,seo/keywords/suggestions(expand each service into the real procedure questions and "[service] [city]" queries patients type, with the "people also ask"/autocomplete variants),seo/keywords/intent(classify each query — informational vs commercial/transactional — so closeness-to-booking is a read signal, not a guess). - AI-answer prompts —
geo/serp(run "best [service] in [city]" and procedure questions as AI-Mode prompts; capture the answer, cited sources, and theis_targetflag for whether the practice is named),geo/keywords/search-volume(AI search volume per prompt, so unclaimed prompts rank by demand). - Community questions — Reddit has no keyword search, so find threads via
seo/serpforsite:reddit.com <procedure>(e.g.site:reddit.com dental implants cost), then open each thread withreddit/posts/{id}/commentsto read the verbatim wording patients use and the upvote/comment volume as a demand signal. - Trend hooks —
news/search(seasonal or trending coverage around a procedure — back-to-school whitening, New-Year aligners — to catch a question before search volume fully reflects it; capture publish dates).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 94 lines · 95 tokens per session scan A 6d9b2bec4835
patient-question-content is a skill published in the GitHub repository unifapi-agent/agents (559 stars, last pushed 2d ago), licensed MIT. It adds 95 tokens to every session and 1,900 once invoked, about $0.0005 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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