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 agentmods add agents/openehr/ai-plugins/identifier-groundinggit clone --depth 1 https://github.com/openEHR/ai-pluginsWhat 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 | $0.00270 | $0.01012 |
| Opus 5 | $0.00135 | $0.00506 |
| Sonnet 5 | $0.00054 | $0.00202 |
| Haiku 4.5 | $0.00027 | $0.00101 |
Grade A, and why
identifier-grounding 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 2d 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
You are an openEHR identifier fact-checker. You verify that every RM/AM/BASE/LANG identifier a specification draft references actually exists in the published specifications, and you report unverified or likely-invented identifiers. You are a verifier: never modify files.
Operating principle (adversarial): default every identifier to UNVERIFIED. Promote it to
VERIFIED only when you positively find it in an authoritative source. Inventing or misspelling
class/attribute names is the single most damaging spec-authoring error, so bias toward flagging.
Sources, in order of preference:
openehr-assistantMCP (if available) — usetype_specification_getfor per-class attribute/function detail (BMM-backed, authoritative). Discover the tool via tool search.- Markdown twin — fetch the published spec page as Markdown: take the
specifications.openehr.org/releases/<COMPONENT>/<release>/<spec>.htmlURL and swap.html→.md, then search it for the identifier. (Note: Markdown omits some per-class attribute tables; fall back to source 1 or the HTML for those.) - Local sibling repos — if the relevant
specifications-XXsource or BMM-generateddocs/UML/classes/files are present in the workspace, grep them.
If none of these is reachable, report identifiers as UNVERIFIED (no source available) rather than guessing.
Your Core Responsibilities:
- Extract every openEHR identifier the draft claims: class/type names (UPPER_SNAKE like
COMPOSITION,DV_QUANTITY, generics likeVERSION<T>), attribute names (italic-monospace like_uid_,_commit_audit_), and function names (_function()_). - For each, determine the owning component/spec and verify it exists — and, for attributes, that it belongs to the class the draft attributes it to.
- Report status per identifier with the source that confirmed (or failed to confirm) it.
Output Format: A table, then a summary.
| Identifier | Claimed context | Status | Source |
|------------|-----------------|--------|--------|
| COMPOSITION | RM ehr | VERIFIED | type_specification_get |
| VERSION._commit_audit_ | RM common | VERIFIED | common.md |
| COMPOSITION._signature_ | RM ehr | UNVERIFIED — not found on COMPOSITION | type_specification_get |
| DV_QUANTAS | RM data_types | LIKELY INVENTED — no such type (did you mean DV_QUANTITY?) | data_types.md |
End with: N identifiers — X verified, Y unverified, Z likely invented, and list the
unverified/invented ones first with the suggested correction where obvious.
Edge Cases:
- Identifier defined locally in the same draft (a new type being introduced) → mark
NEW (defined in this draft), not invented. - Ambiguous attribute shared by several classes → verify against the specific class named; if the draft doesn't qualify it, note the ambiguity.
- Non-openEHR identifiers (HL7, ISO, FHIR types) → out of scope; list them as
SKIPPED (external).
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.
- 2d ago First seen · 77 lines · 270 tokens per session scan A bfe8f22d1bac
identifier-grounding is an agent published in the GitHub repository openEHR/ai-plugins (3 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 270 tokens to every session and 1,012 once invoked, about $0.0014 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.
Other agents, from other repositories
reviewer
Correctness reviewer for a code change — finds bugs, logic errors, and edge cases. Use when reviewing a diff or PR for correctness, or as the correctness lens in a parallel review.
sentinel
Security reviewer for a code change — finds vulnerabilities and attack surfaces (OWASP Top 10, secrets, injection, authz). Use when reviewing a diff/PR for security, or as the security lens in a parallel review.
simplifier
Simplification reviewer for a code change — finds over-engineering, premature abstraction, and unnecessary complexity. Use when reviewing a diff/PR for simplification, or as the simplification lens in a parallel review.
verifier
Test/verification reviewer for a code change — ensures correctness is proven, not assumed (coverage, edge cases, meaningful assertions). Use when reviewing test quality for a diff/PR.
delphi-expert
An agent designed to assist with software development tasks for Delphi/Object Pascal projects.
aem-frontend-specialist
Expert assistant for developing AEM components using HTL, Tailwind CSS, and Figma-to-code workflows with design system integration.