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Radiology Consensus Guideline

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huang-sir1
radiology-consensus-guideline

Design/audit consensus and evidence-to-recommendation products; not review synthesis or endorsement.

Overview

Publisherhuang-sir1
Repositoryradiology-skills
Skill nameradiology-consensus-guideline
Stars
2K
Forks
20
Bundled files
9
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.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by huang-sir1 on GitHub. Read the source before you install it.

Installation

Install the Radiology Consensus Guideline 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.
    https://github.com/huang-sir1/radiology-skills/tree/main/radiology-skills/skills/radiology-consensus-guideline
  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/huang-sir1/radiology-skills.git /tmp/radiology-skills
mkdir -p .claude/skills
cp -r /tmp/radiology-skills/radiology-skills/skills/radiology-consensus-guideline .claude/skills/radiology-consensus-guideline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Radiology Consensus Guideline 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 Radiology Consensus Guideline 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 Radiology Consensus Guideline 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.

Radiology Consensus and Guideline Development

Use this skill to design, run-plan or audit a consensus statement, appropriateness project, practice parameter, technical standard or clinical practice guideline. It owns the panel/process, evidence-to-decision record, consensus protocol, recommendation ledger and lifecycle plan. It does not perform the underlying systematic review, confer society endorsement, set a legal standard of care or let expert voting substitute for evidence.

Choose the product and mode

First declare the product: clinical-practice-guideline, appropriateness-criteria, practice-parameter, technical-standard, expert-consensus-statement or research-priority/definition-consensus. Do not use these labels interchangeably.

ModeUse whenRequired result
scopingproduct, users, questions or authority are unsettledscope, product decision, stakeholders, evidence needs and stop conditions
protocola versioned development plan is needed before evidence/panel decisionspanel, COI, evidence, consensus, consultation and update protocol
evidence-to-decisiona frozen evidence synthesis must become recommendation judgmentsGRADE/compatible EtD ledger with explicit uncertainty
formal-consensusDelphi, RAND/UCLA or nominal group work is planned or auditedprespecified rounds, thresholds, denominator, feedback, dissent and reporting record
audit-update-retirean existing statement/guideline is reviewed for trustworthiness or currencymethod audit, surveillance result, update/retirement and supersession map

Read references/evidence-to-recommendation.md for the systematic-review handoff, GRADE/EtD and recommendation wording. Read references/formal-consensus-methods.md only for a formal consensus exercise. Read references/radiology-guidance-lifecycle.md for appropriateness criteria, practice parameters, technical standards, implementation, updating and retirement. Verify methods and authority through references/source-registry.md.

Input passport

Record:

product and mode | sponsor/developer and actual adoption authority | jurisdiction/organization | scope, population, modality/test/intervention/comparator/outcomes/setting | intended users and affected people | panel roles, patient/public members and COI records | frozen systematic-review handoff/version/currency | certainty framework | consensus method and prespecified rule | draft and consultation artifacts | implementation context | publication/update/retirement owner | user authority for edits or external communication.

Missing adoption authority, panel decisions, COI management, patient/public participation, evidence certainty or official status remains NOT_VERIFIED. Advisory drafting is not an endorsed guideline.

Choose the evidence lane for the declared product. A clinical recommendation presented as evidence-based requires the relevant systematic-review/EtD handoff. A research-priority or definition-consensus exercise instead requires transparent item generation, search/mapping or stakeholder evidence, panel judgments and limits; use NOT_APPLICABLE_GRADE when it makes no clinical-effect or recommendation-strength claim. A generic Delphi protocol does not require an invented effect synthesis or GRADE rating.

Core evidence and recommendation states

  • Evidence handoff: EVIDENCE_READY, EVIDENCE_PARTIAL, EVIDENCE_ABSENT or EVIDENCE_STALE.
  • Recommendation: DRAFT, CONDITIONAL, STRONG, NO_RECOMMENDATION, RESEARCH_ONLY, SUPERSEDED or RETIRED only when defined by the selected framework and authorized process.
  • Consensus result: CONSENSUS_REACHED, CONSENSUS_NOT_REACHED, STABLE_DISAGREEMENT, ATTRITION_LIMITED or NOT_ASSESSABLE.

Evidence certainty, recommendation strength and consensus percentage are different fields. A high vote does not upgrade low/absent evidence, and a low-certainty body does not automatically prohibit a strong recommendation when a transparent framework supports an exceptional case.

Required workflow

  1. Lock the product and authority. Define who will use the output, for which decision, and who can officially adopt/endorse it. Use “draft” or “advisory” until a verified process confers status.
  2. Scope the decision. Specify population, imaging scenario, modality/test, comparator, downstream action, patient-important outcomes, setting, exclusions and equity/access questions.
  3. Constitute the panel. Include relevant clinical disciplines, radiologists, referrers, technologists/medical physicists when technical decisions are material, methodologists, implementers and patients/public or other affected representatives. Record balance, recruitment, roles, COI assessment, management and recusals.
  4. Accept the product-appropriate evidence handoff. For an evidence-based clinical recommendation, require search currency, study-family/effect-row identity, risk-of-bias/ applicability, synthesis and certainty from radiology-systematic-review. For priorities or definitions, record item sources, mapping/search limits, stakeholder input and traceable revision; a full effect review is required only if the intended claim needs it. Do not relabel selected references or panel memory as a systematic review.
  5. Run the applicable decision process. For clinical recommendations, record benefits/harms, certainty, values/preferences, resources, equity, acceptability and feasibility. Link diagnostic accuracy to downstream management and patient outcomes. For priorities or definitions, report explicit selection criteria, content/semantic judgments and dissent without inventing clinical effects, GRADE certainty or recommendation strength.
  6. Use formal consensus only for its declared purpose. Prespecify method, panel, rounds, anonymity/interactions, feedback, denominator, threshold, stability, attrition, tie/disagreement handling and stopping. Use templates/consensus-guideline-protocol.md.
  7. Draft atomic recommendations or consensus items. Each clinical recommendation states population/scenario, action, comparator/conditions, strength, certainty, rationale, harms/burden, implementation conditions, exceptions, dissent and research gaps. Use templates/recommendation-etd-ledger.md. For priorities/definitions, use the item register and formal-consensus result sections instead; include wording, provenance, scope, rationale and status, with clinical EtD fields not applicable.
  8. Consult and quality-control. Preserve stakeholder comments, responses, panel changes, unresolved disagreement and external review. Reporting-checklist completion does not prove method quality or endorsement.
  9. Plan implementation and lifecycle. Define dissemination, feasibility tools, monitoring, surveillance, update triggers, versioning, supersession and retirement. Imaging technology, contrast/tracers, dose, reconstruction, AI versions and clinical standards can make guidance stale.

Stop and escalation gates

Return GUIDANCE_STOP_AND_REFRAME when product or adoption authority is misrepresented; scope or decision scenarios are undefined; the evidence packet is missing/stale for a claim presented as evidence-based; material panel COI cannot be managed; affected patients/public or essential disciplines are systematically excluded without justification; consensus thresholds are chosen after results; attrition, dissent or denominator is hidden; expert votes are used to manufacture evidence; or a current clinical recommendation could expose patients to unreviewed harm.

Escalate formal endorsement, legal/regulatory interpretation and individual patient decisions to the responsible society, institution, regulator or clinical team. The skill may prepare evidence and drafts but cannot adopt, endorse or implement official guidance.

Output contract

  1. Product, scope and authority passport
  2. Panel/stakeholder/patient-public and COI matrix
  3. Product-appropriate evidence handoff and currency verdict — systematic review for the clinical evidence claim, or item-generation/mapping/stakeholder evidence for priorities and definitions
  4. Question/outcome and imaging-scenario map
  5. GRADE or compatible evidence-to-decision ledger when applicable; otherwise NOT_APPLICABLE_GRADE plus the item-selection/definition rationale
  6. Consensus protocol and result — rounds, thresholds, denominator, attrition and dissent
  7. Recommendation or consensus-item ledger — strength, certainty and consensus kept separate; clinical strength/certainty is not invented for a terminology or research-priority item
  8. Implementation, equity, monitoring and research-gap plan
  9. Consultation, external-review and change-response record
  10. Version, update, supersession and retirement plan with exact non-endorsement boundary

Handoffs and non-ownership

  • Search, screening, extraction, risk of bias, synthesis and evidence certainty -> radiology-systematic-review; current clinical facts -> radiology-clinical-domain.
  • Quantitative Delphi/RAND agreement or comparative inference -> radiology-stats; CEA/CUA, budget impact, ICER/QALY, PSA/VOI and economic-model evidence consumed by an EtD -> radiology-health-economics. This skill weighs the supplied economic evidence in a recommendation; it does not build or authorize the economic model.
  • Reporting guideline/quality checklist -> radiology-reporting; prose, tables, figures and decks -> their artifact owners.
  • Society boards, institutions, regulators and clinical teams retain endorsement, adoption, implementation, legal and patient-care authority.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Radiology Consensus Guideline AI skill do?

Design/audit consensus and evidence-to-recommendation products; not review synthesis or endorsement.

Why use Radiology Consensus Guideline on TypingMind?

Because you install it once and use it with any model. Radiology Consensus Guideline 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 Radiology Consensus Guideline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/huang-sir1/radiology-skills/tree/main/radiology-skills/skills/radiology-consensus-guideline. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Radiology Consensus Guideline?

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 Radiology Consensus Guideline?

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

Is the Radiology Consensus Guideline AI skill free?

It is published on GitHub by huang-sir1. Check the repository for licensing terms. 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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