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 aizech/clinical-skills --skill image-quality-auditgit clone --depth 1 https://github.com/aizech/clinical-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/aizech/clinical-skills/image-quality-audit)<a href="https://agentmods.dev/skills/aizech/clinical-skills/image-quality-audit"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/image-quality-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/aizech/clinical-skills/image-quality-audit"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/image-quality-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 | $0.00055 | $0.00462 |
| Opus 5 | $0.00028 | $0.00231 |
| Sonnet 5 | $0.00011 | $0.00092 |
| Haiku 4.5 | $0.00006 | $0.00046 |
Grade A, and why
image-quality-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 10d 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.
What it actually says
Image Quality Audit Skill
Triggers
- "image quality audit"
- "artifact review"
- "dose analysis"
- "protocol deviation"
- "quality metrics"
- "diagnostic adequacy"
- "technique optimization"
Parameters
audit_type(required): Type of quality assessmentartifact- Motion, noise, streak artifactsdose- Radiation dose optimization and DRL complianceprotocol- Protocol adherence and deviation analysisadequacy- Diagnostic sufficiency for intended purposetechnique- Technical parameters reviewcomprehensive- Full quality review
modality(required): Imaging modality to audittime_range(optional): Audit period - defaults to last 7 dayssample_size(optional): Studies to review - defaults to all in rangeseverity_threshold(optional): Minimum severity to flag
Evaluation Criteria
- Artifacts: Type, severity (1-5), impact on diagnostic utility
- Dose: DLP, CTDIvol vs. ACR reference levels, size-adjusted metrics
- Protocol: Coverage completeness, sequence selection, contrast timing
- Adequacy: Signal-to-noise, spatial resolution, positioning
Output Format
Returns structured JSON with:
- Quality metrics summary
- Severity distribution
- Contributing factors analysis
- Improvement recommendations ranked by impact
- Training priorities for technologist/site issues
Usage Examples
audit_type: artifact
modality: CT
time_range: last_week
severity_threshold: 3
audit_type: dose
modality: CT
time_range: last_month
Standards Reference
- ACR Physical Parameters for CT, MRI, Ultrasound, Mammography
- ICRP and ACR dose reference levels
- modality-specific practice guidelines
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.
- 10d ago First seen · 66 lines · 55 tokens per session scan A 65df6f883f8a
image-quality-audit is a skill published in the GitHub repository aizech/clinical-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 462 once invoked, about $0.0003 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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