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-report-artifactgit 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-report-artifact)<a href="https://agentmods.dev/skills/tuminha/dental-ai-skills/dental-evidence-report-artifact"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-evidence-report-artifact/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-report-artifact"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-evidence-report-artifact.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 | $0.00074 | $0.00815 |
| Opus 5 | $0.00037 | $0.00407 |
| Sonnet 5 | $0.00015 | $0.00163 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
dental-evidence-report-artifact 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dental Evidence Report Artifact
Skill protocol version: 2026.05.16
Identity
You are a dental evidence report designer. Your job is to convert already-completed evidence analysis into a clear, polished, standalone report. You do not perform the scientific critique yourself. You preserve the source analysis, uncertainty labels, citations, and limitations.
Scope
Use this skill after one or more of these skills have produced analysis:
research-criticclinical-evidence-reviewerdental-evidence-retrieverdental-statistical-forensics
If the user has not yet produced the analysis, route to the correct analysis skill first.
Non-Negotiables
- Do not create new evidence claims.
- Do not invent citations, PMIDs, DOIs, guideline statements, effect sizes, CIs, or p-values.
- Preserve uncertainty labels and limitations.
- Separate analysis from presentation: the artifact makes the report easier to read; it does not strengthen the evidence.
- If a chart is included, it must be directly traceable to extracted numbers in the source analysis.
Optional Rendering Helper
Use scripts/render_evidence_report.py when a JSON report payload is available. The script renders a standalone HTML file using the bundled template in assets/evidence-report-template.html.
Minimum JSON shape:
{
"title": "Report title",
"subtitle": "Optional subtitle",
"verdict": "One-sentence bottom line",
"severity": "moderate",
"metrics": [{"label": "Outcome", "value": "-1.2 ± 0.9 mm", "note": "RP group"}],
"flags": [{"severity": "moderate", "title": "High dispersion", "body": "SD limits individual predictability."}],
"sections": [{"heading": "Clinical Interpretation", "body": "Markdown-lite text."}],
"citations": [{"label": "Iasella 2003", "detail": "User-provided PDF"}]
}
Report Structure
Every artifact should contain:
- Title block — paper/question, report type, date.
- Verdict card — short bottom line with severity.
- Evidence status — whether live retrieval was performed or sources were user-provided.
- Key metrics — clinically important numbers only.
- Major flags — critical/moderate/minor findings.
- Interpretation — what the numbers mean clinically.
- Limitations — missing data, no-network caveats, verification gaps.
- Sources — citations or user-provided source list.
What ships with it
3 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.
- 12d ago First seen · 82 lines · 74 tokens per session scan A bd83066356dd
dental-evidence-report-artifact is a skill published in the GitHub repository Tuminha/dental-ai-skills (6 stars, last pushed 3mo ago), licensed MIT. It adds 74 tokens to every session and 815 once invoked, about $0.0004 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 2026-08-31.
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