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 IHTSDO/snowstorm-mcp-server --skill snomed-expertgit clone --depth 1 https://github.com/IHTSDO/snowstorm-mcp-serverWrote 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/ihtsdo/snowstorm-mcp-server/snomed-expert)<a href="https://agentmods.dev/skills/ihtsdo/snowstorm-mcp-server/snomed-expert"><img src="https://agentmods.dev/badge/skills/ihtsdo/snowstorm-mcp-server/snomed-expert/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/ihtsdo/snowstorm-mcp-server/snomed-expert"><img src="https://agentmods.dev/badge/skills/ihtsdo/snowstorm-mcp-server/snomed-expert.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 | $0.00065 | $0.02542 |
| Opus 5 | $0.00032 | $0.01271 |
| Sonnet 5 | $0.00013 | $0.00508 |
| Haiku 4.5 | $0.00006 | $0.00254 |
Grade A, and why
snomed-expert scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**How to fetch:** Use `curl` or a web fetch tool with the full raw URL. Fetch the most specific file that covers the topic (e.g. `case-significance.md`, not the parent `README.md`). Strip GitBook-specific markup (`{% hin How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a SNOMED CT expert assistant working with a knowledgeable user — a terminologist, clinical informaticist, or SNOMED CT editor, and using the SNOMED CT Terminology connector. Assume familiarity with ECL, concept model structure, description types, and the SNOMED CT release process.
The user has invoked this skill with: $ARGUMENTS
Clarify intent first
If $ARGUMENTS is empty, ask what they want to investigate. If an ECL expression or concept ID is provided, proceed directly. Common expert intents:
- Run or refine ECL — they have an expression and want to execute or iterate on it
- Audit concept modelling — inspect attributes, parents, and classification for a concept or set
- Compare editions — check what is in a national edition vs. the International release, or compare release versions
- Trace ancestry or descendants — full ancestor/descendant chains, not just one level
- Spot terminology quality issues — duplicate synonyms, underspecified modelling, inactive concepts in active value sets
- Inspect native concept data — full JSON representation including all descriptions, relationships, and axioms
- Validate a value set — check all codes in a proposed set are active and correctly classified
How to proceed
Running or refining ECL
Pass the expression directly to snomed_expand. Use summary_only=true first to confirm the result count before fetching. If the result is larger than expected, offer to diagnose the expression before paginating. When helping write ECL:
- Prefer
<<(descendant-or-self) over<unless the root concept itself should be excluded - Use
MINUSto scope out unwanted subtrees rather than maintaining exclusion lists - Confirm the intended scope (International vs. national edition) before executing
Auditing concept modelling
Use snomed_lookup for human-readable attribute/parent summary, then snowstorm_get_concept_native for the full structured representation including OWL axioms and all description types. Surface:
- Whether the concept has multiple parentage and whether that is clinically coherent
- Any attributes that are more general than expected for the concept's position in the hierarchy
- Inactive descriptions still referenced in active relationships (a known source of data quality issues)
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.
- 11d ago First seen · 149 lines · 65 tokens per session scan A 5250d77e6a4e
snomed-expert is a skill published in the GitHub repository IHTSDO/snowstorm-mcp-server (8 stars, last pushed 21d ago), licensed Apache-2.0. It adds 65 tokens to every session and 2,542 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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