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 Cadasto/openehr-assistant-plugin --skill aql-authoringgit clone --depth 1 https://github.com/Cadasto/openehr-assistant-pluginWrote 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/cadasto/openehr-assistant-plugin/aql-authoring)<a href="https://agentmods.dev/skills/cadasto/openehr-assistant-plugin/aql-authoring"><img src="https://agentmods.dev/badge/skills/cadasto/openehr-assistant-plugin/aql-authoring/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/cadasto/openehr-assistant-plugin/aql-authoring"><img src="https://agentmods.dev/badge/skills/cadasto/openehr-assistant-plugin/aql-authoring.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 | $0.00102 | $0.01785 |
| Opus 5 | $0.00051 | $0.00892 |
| Sonnet 5 | $0.00020 | $0.00357 |
| Haiku 4.5 | $0.00010 | $0.00178 |
Grade A, and why
aql-authoring 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.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AQL Authoring
The inline syntax below is a quick crib. The
aql/syntaxguide loaded in Step 1 is authoritative — if they ever disagree, follow the guide.
Step 1: Load Guides (MANDATORY)
Before writing or reviewing any AQL query, load the authoritative guides:
guide_get("openehr://guides/aql/principles")
guide_get("openehr://guides/aql/syntax")
guide_get("openehr://guides/aql/idioms-cheatsheet")
Consult worked examples (when applicable)
When the user asks for a query to adapt, or when the clinical question matches a common pattern (cohort selection, pagination with total count, time-window filtering, cross-composition joins, terminology value-set matching, "latest per EHR", ISM-state filtering), try examples_search(kind="aql") before drafting. The curated AQL examples are under openehr://examples/aql/{name} and include pattern metadata and related-spec links — reuse and adapt rather than invent. Skip this step if the question is clearly novel or the user already provided the skeleton.
Step 2: Understand the Data Model
AQL queries operate on archetypes. Before writing a query:
- State assumptions about deployed templates/archetypes — verify path endpoints and RM types against the deployed template, not display labels; when a deployed template is named, fetch it (
ckm_template_search→ckm_template_get) rather than guessing paths - Identify which archetypes contain the required data (
ckm_archetype_searchwhen the archetype id is not yet known) - Load the archetype to understand its path structure:
ckm_archetype_get("<archetype-id>") - Use
type_specification_getto clarify RM type details when needed
Step 3: AQL Syntax
Basic Structure
SELECT <paths>
FROM EHR e
CONTAINS COMPOSITION c[openEHR-EHR-COMPOSITION.<name>.v1]
CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.<name>.v1]
WHERE <conditions>
ORDER BY <paths>
Containment
Define the archetype hierarchy using CONTAINS:
FROM EHR e
CONTAINS COMPOSITION c
CONTAINS OBSERVATION o[openEHR-EHR-OBSERVATION.blood_pressure.v2]
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 · 171 lines · 102 tokens per session scan A 1bbf49f49264
aql-authoring is a skill published in the GitHub repository Cadasto/openehr-assistant-plugin (4 stars, last pushed 15d ago), licensed MIT. It adds 102 tokens to every session and 1,785 once invoked, about $0.0005 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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