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Ask Openmed

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maziyarpanahi
ask-openmed

Choose the first OpenMed workflow skill for an intake, privacy, extraction, exchange, or verification request using deterministic local routing. Use when a goal is broad, spans several clinical-data stages, or leaves the data-sensitivity status unclear; the privacy gate is selected before downstream work when raw clinical or personal content may be present.

Overview

Publishermaziyarpanahi
Repositoryopenmed
Skill nameask-openmed
Stars
5.3K
Forks
677
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by maziyarpanahi on GitHub. Read the source before you install it.

Installation

Install the Ask Openmed AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/maziyarpanahi/openmed.git /tmp/openmed
mkdir -p .claude/skills
cp -r /tmp/openmed/skills/ask-openmed .claude/skills/ask-openmed
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ask Openmed in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ask Openmed on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ask Openmed is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Ask OpenMed

Use this skill as the first pass when a request does not name a focused OpenMed workflow. It selects an existing skill identifier; it does not process input, download a model, call a service, or make a clinical decision. No mandatory network call is part of this route.

Deterministic routing contract

Apply these rules in order:

  1. Normalize only the stated goal: lowercase it, trim surrounding whitespace, and collapse repeated whitespace. Do not inspect or copy the data payload.
  2. Apply the intake boundary. If the goal matches an Intake row, select the first matching intake skill even when the goal also names a later stage. If sensitivity is unclear, its next handoff is the privacy gate: deidentifying-clinical-text, before extraction, exchange, or verification sees the parsed content.
  3. For a goal with no intake cue, apply the privacy override. If it asks to analyze, extract, exchange, share, upload, or verify clinical or personal content and is not explicitly marked safe, start at the privacy gate. The only safe markers are synthetic input, synthetic note, synthetic record, synthetic dataset, input is synthetic, data is synthetic, already de-identified, and already deidentified. A marker does not count when no, not, never, unknown, or uncertain occurs in the four normalized words before it. Treat every ambiguous safety statement as sensitive.
  4. Otherwise inspect the remaining tables in the fixed handoff order shown below. Treat each comma-separated cue as a case-insensitive substring of the normalized goal, and select the first matching row. Every cue cell is a comma-separated list of alternatives; conjunctions have no special meaning. Do not add synonyms or infer cues from the payload. This stage order and row order break every tie.
  5. If no row matches, use building-with-openmed as the orientation fallback.

Route output should contain only the selected category, skill identifier, matched rule index, and next handoff. Never echo the request, input values, exception text, or detected spans into a log or report.

For a multi-stage request, route one stage at a time in this fixed handoff order: intake → privacy → extraction → exchange → verification. A later stage does not bypass the privacy gate merely because it was named first.

Intake

Choose the first skill for turning an external document or record format into local, processable input.

Goal cuesFirst skillContinue with
laboratory table, lab tableextracting-lab-tablesprivacy, then verification
scan, fax, image, PDF, CSV, table, document OCRingesting-clinical-documentsprivacy, then extraction
C-CDA, CCD, CDA XMLparsing-ccda-documentsprivacy, then extraction
HL7 v2, ADT, ORU, MDM, OBX, pipe-delimited feedparsing-hl7v2-messagesprivacy, then extraction
DICOM header, DICOM-SR metadataextracting-dicom-metadataprivacy, then extraction
pull FHIR records, page FHIR records, FHIR serverfetching-fhir-resourcesprivacy, then extraction

Privacy

Use the privacy table both for an explicit privacy goal and for the privacy override. The first row is the default gate for unspecified sensitive input.

Goal cuesFirst skillContinue with
remove clinical identifiers, mask clinical identifiers, redact clinical text, anonymize clinical text, de-identify clinical textdeidentifying-clinical-textextraction or exchange
find identifiers, detect identifiers, PII entitiesextracting-pii-entitiesde-identification or review
privacy policy, privacy profileconfiguring-privacy-policiesde-identification
PHI in logs, PHI in errors, PHI in telemetry, no-PHI loggingenforcing-nophi-loggingverification
de-identify non-English text, multilingual de-identificationdeidentifying-multilingual-textextraction
stable pseudonyms, approved linkage pseudonymspseudonymizing-for-gdprverification

Extraction

Choose the focused skill after intake and privacy handling when the request is about finding or structuring clinical meaning.

Goal cuesFirst skillContinue with
diseases, drugs, anatomy, genes, clinical NERextracting-clinical-entitiesexchange or verification
custom entity labels, zero-shot extractionrunning-zeroshot-nerexchange or verification
housing, food, work, transport, SDOHextracting-sdohverification
lab values, units, reference ranges, abnormal flagsparsing-lab-valuesterminology or exchange
radiology findings, radiology measurements, radiology impressionstructuring-radiology-reportsexchange or verification
note sections, clinical sections, section segmentationsegmenting-clinical-sectionsextraction

Exchange

Choose an exchange skill only after the source is safe to handle. These skills may use a user-supplied endpoint or terminology service; this router itself performs no network call.

Goal cuesFirst skillContinue with
FHIR R4 resources, export to FHIRexporting-to-fhirbundle or conformance verification
FHIR transaction Bundle, FHIR batch Bundleassembling-fhir-bundlesconformance verification
FHIR Bulk Data export, bulk FHIRexporting-bulk-fhirprivacy, then extraction
SMART-on-FHIR app, SMART-on-FHIR launchscaffolding-smart-on-fhirconformance verification
terminology validation, terminology expansion, terminology translation, terminology serverquerying-terminology-serviceexchange or verification

Verification

Use verification routes for a stated release, safety, leakage, audit, risk, or conformance check. If the source is not explicitly safe, the privacy override still wins first.

Goal cuesFirst skillDecision or handoff
residual identifiers, de-identification leakageauditing-deid-leakageblock release on a finding
de-identification audit trail, no-PHI audit trailauditing-deidentification-runsretain offsets, hashes, and provenance
leakage gate, release leakageevaluating-with-leakage-gatesfail closed on leakage
re-identification risk, k-anonymity, quasi-identifiersreviewing-reidentification-riskreview residual risk
Safe Harborauditing-safe-harbor-checklistreview the no-PHI report
FHIR US Core, USCDI conformancevalidating-us-corecorrect the resource before exchange
HIPAA privacy checklist, HIPAA security checklistchecking-hipaa-complianceaddress gaps before release

Ambiguous goals and escalation examples

Use the privacy override and the fixed handoff order for ambiguous requests:

These are routing examples only. Keep all demonstrations synthetic or placeholder-based, and keep route diagnostics free of source content.

Frequently asked questions

What does the Ask Openmed AI skill do?

Choose the first OpenMed workflow skill for an intake, privacy, extraction, exchange, or verification request using deterministic local routing. Use when a goal is broad, spans several clinical-data stages, or leaves the data-sensitivity status unclear; the privacy gate is selected before downstream work when raw clinical or personal content may be present.

Why use Ask Openmed on TypingMind?

Because you install it once and use it with any model. Ask Openmed is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ask Openmed in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/maziyarpanahi/openmed/tree/master/skills/ask-openmed. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ask Openmed?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ask Openmed?

As many as you like. As long as a model supports skills, you can use Ask Openmed with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ask Openmed AI skill free?

Yes. It is published on GitHub by maziyarpanahi under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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