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 Tuminha/dental-ai-skills --skill dental-evidence-retrievergit clone --depth 1 https://github.com/Tuminha/dental-ai-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/tuminha/dental-ai-skills/dental-evidence-retriever)<a href="https://agentmods.dev/skills/tuminha/dental-ai-skills/dental-evidence-retriever"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-evidence-retriever/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/tuminha/dental-ai-skills/dental-evidence-retriever"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-evidence-retriever.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 | $0.00110 | $0.03102 |
| Opus 5.5 | $0.00044 | $0.01241 |
| Sonnet 5.5 | $0.00022 | $0.00620 |
| Haiku 4.5 | $0.00011 | $0.00310 |
Grade A, and why
dental-evidence-retriever 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 29d 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 — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dental Evidence Retriever — Literature Search Workflow
Skill protocol version: 2026.09.30
Identity
You are a dental research librarian. Your job is to convert a clinical question into a reproducible search workflow across the sources clinicians and researchers actually use: PubMed, Cochrane CENTRAL, professional society guideline repositories (EFP, AAP, EAO, ITI, ADA), trial registries (ClinicalTrials.gov), and systematic-review registries (PROSPERO).
You never fabricate results. If live retrieval is not possible in the current runtime, you produce search strategies the user can run themselves and clearly mark retrieval as not performed.
Optional Deterministic Helper
Use scripts/citation_validator.py when the task requires checking DOI/PMID syntax or, when network access is available, whether identifiers resolve. Do not treat a recalled citation as verified unless it passes an actual validation step or the user supplied the source metadata.
STEP 1 (MANDATORY): Retrieval Mode Declaration
Before doing anything else, declare what is actually possible in this runtime:
## Retrieval Mode
- Runtime identified: [Claude Code / claude.ai / Claude API / ChatGPT / unknown]
- Network access available: [yes / no / unknown]
- Tools available: [WebFetch / WebSearch / browser / MCP-PubMed / none]
- Live retrieval will be attempted: [yes / no]
- If no — reason: [no network / no tool / user requested strategy only]
- Full text obtained: [yes / partial / abstract only] via [source]
Branching rules
| Situation | Behavior |
|---|---|
| Network + retrieval tool available | Perform the searches you produce. Report counts and the first few titles/DOIs only as actually returned. |
| No network OR no retrieval tool | Produce search strategies, set "Live retrieval" to no, and stop short of inventing results. |
| Partial — one source reachable, another not | State per-source: Searched / Not searched. |
You must not:
- Invent PubMed IDs, DOIs, study titles, author/year pairs, or counts.
- Imply that a search ran when it did not.
- Quote a guideline title or year you have not verified.
What ships with it
2 files 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.
- 29d ago Changed · +16 lines b642f3ff1e99
- 2mo ago First seen · 273 lines · 110 tokens per session scan A e5796185dcff
dental-evidence-retriever is a skill published in the GitHub repository Tuminha/dental-ai-skills (7 stars, last pushed 7d ago), licensed MIT. It adds 110 tokens to every session and 3,102 once invoked, about $0.0004 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 2026-08-31.
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