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 openEHR/ai-plugins --skill regen-classesgit clone --depth 1 https://github.com/openEHR/ai-pluginsWrote 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/openehr/ai-plugins/regen-classes)<a href="https://agentmods.dev/skills/openehr/ai-plugins/regen-classes"><img src="https://agentmods.dev/badge/skills/openehr/ai-plugins/regen-classes/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/openehr/ai-plugins/regen-classes"><img src="https://agentmods.dev/badge/skills/openehr/ai-plugins/regen-classes.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 | $0.00022 | $0.00929 |
| Opus 5.5 | $0.00009 | $0.00372 |
| Sonnet 5.5 | $0.00004 | $0.00186 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
regen-classes 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 7d 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
Regenerate the class tables and UML diagrams for $ARGUMENTS with bmm-publisher, from the BMM files in
the component repo at the current directory, not from the copies bundled in the image (they lag the
repos, and a run from a bundled id exits 0 while rendering the older model). The arguments are a schema
id without .bmm.json (for example openehr_rm_1.2.0) plus any -d <dependency-schema-id> flags (RM
depends on BASE: openehr_rm_1.2.0 -d openehr_base_1.3.0). The layouts and the placement into
docs/UML/ are in the openehr-specs:class-generation skill; this wrapper covers generation only.
If $ARGUMENTS is empty, ask for the schema id and stop.
- Read
manifest.jsonid(or take the directory namespecifications-<id>). In the ITS-XML, ITS-BMM, ITS-JSON and ITS-REST repos, say that they hold no model of their own and thatbmm-publisheris not run there, and stop. ITS-BMM regenerates its ODIN and YAML with its ownmake generate. - Run
docker --version. If Docker is missing, say it is required (the image and its dev container both run on it) and stop. - Map each id to its file and Glob that it exists: the schema to
computable/BMM/<id>.bmm.json, and a dependencyopenehr_<component>_<version>to the sibling clone's../specifications-<COMPONENT>/computable/BMM/<id>.bmm.json(component upper-cased). If one is missing, name it and stop; never fall back to the bundled id. - Write to
./outunless the user names another target. Ask before writing into aspecifications-XXrepo'sdocs/UML/. - Pick the command by layout (step 2 of the
class-generationworkflow):legacy-adoc -o /app/output/UML/classeswhen the spec's chapters containinclude::{uml_export_dir}/classes/(the tables land in./out/UML/classes), otherwiseasciidoc. Mount each file read-only under/in/, pass the paths, and map output ownership to the host user (RM with BASE shown):
Add one mount and onedocker run --rm --user $(id -u):$(id -g) \ -v "$PWD/computable/BMM/openehr_rm_1.2.0.bmm.json":/in/openehr_rm_1.2.0.bmm.json:ro \ -v "$PWD/../specifications-BASE/computable/BMM/openehr_base_1.3.0.bmm.json":/in/openehr_base_1.3.0.bmm.json:ro \ -v ./out:/app/output \ ghcr.io/openehr/bmm-publisher asciidoc -v /in/openehr_rm_1.2.0.bmm.json -d /in/openehr_base_1.3.0.bmm.json-d /in/<id>.bmm.jsonper dependency. The-vlog lists each file read: check that every one is under/in/. - List what was produced (
classes/,effective/, diagram SVGs). Do not commit. Generated files are never hand-edited: change the BMM and regenerate. To place the output, follow theclass-generationskill.
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.
- 7d ago Changed · +4 lines 7c30e3d7d176
- 8d ago Changed · +10 lines a5d715628e28
- 9d ago First seen · 36 lines · 22 tokens per session scan A e6255d3f5af4
regen-classes is a skill published in the GitHub repository openEHR/ai-plugins (3 stars, last pushed yesterday), licensed Apache-2.0. It adds 22 tokens to every session and 929 once invoked, about $0.0001 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 2026-10-08.
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clinical-reports
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pptx-posters
Creates and audits editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Used when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.
nwb-conversion
Converts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel…
paper-figures
Extract figures from downloaded papers and include them in survey/review reports. Use when the report covers other groups' work and benefits from their architecture diagrams, experimental plots, or system schematics. Your brain prompt supplies the absolute path to the extract-figures script as {{EXTRACTFIGURES}} — use…
sync-submission
Use when building, auditing or freezing a journal submission package from the canonical manuscript. Detects drift between the source and the per-journal submission copy, builds byte-preserving packages with manifests, and records current, stale or frozen status.