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Write Protocol

Organization
Aperivue
write-protocol

Use when drafting an IRB or ethics research protocol. Writes Background, Study Design, Sample Size and Statistical Plan in full prose and leaves institution-specific sections as TODO skeletons. Filling an institutional Word form is /fill-protocol.

Overview

PublisherAperivue
Repositorymedsci-skills
Skill namewrite-protocol
Stars
349
Forks
82
Bundled files
3
LicenseMIT
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Write Protocol 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/Aperivue/medsci-skills/tree/main/skills/write-protocol
  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/Aperivue/medsci-skills.git /tmp/medsci-skills
mkdir -p .claude/skills
cp -r /tmp/medsci-skills/skills/write-protocol .claude/skills/write-protocol
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Write Protocol 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 Write Protocol 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 Write Protocol 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.

Write-Protocol Skill

Draft the scientific core of an IRB/ethics protocol and leave institution-specific sections as [TODO] skeletons. Read both reference files before generating a protocol draft:

  • ${CLAUDE_SKILL_DIR}/references/protocol_template.md -- the 10-section structure, per-section guidance, and the [TODO] blocks for Sections 5-9
  • ${CLAUDE_SKILL_DIR}/references/ethics_checklist.md -- jurisdiction-specific ethical requirements

Inputs

Collect the required inputs before generating; ask for any that are missing.

  • Required: research question / hypothesis (specific, testable); study type (retrospective cohort, prospective cohort, cross-sectional, RCT, diagnostic accuracy, case-control, case series); target population (who, where, when); primary outcome; secondary outcomes (if any).
  • Optional: key references (DOIs or search terms); institution name (header and ethics guidance); regulatory context -- Korea (PIPA), US (HIPAA/Common Rule), EU (GDPR), other.

Use prior skill outputs directly when they exist; when they do not, ask the user or call the skill:

  • design-study: design recommendations, analysis unit, comparator design, validation strategy.
  • calc-sample-size: protocol/sample_size_justification.md (canonical IRB-ready prose) and protocol/sample_size_calc.{R,py} (reproducible code).
  • search-lit: Background references with verified citations.
  • define-variables: variable_operationalization.md -- literature-grounded definitions, cutoffs, DB-variable mappings for the Methods section. Precondition: if the study is observational and no operationalization artifact exists, call /define-variables before drafting Methods. Do not invent phenotype/cutoff definitions from the data dictionary inside this skill.

Protocol Structure -- 10 Sections

Core Sections (Fully Generated)

Section 1: Background and Rationale (400-600 words)

Full paragraphs, no bullet points, flowing from clinical context (disease burden, current practice) through the knowledge gap and rationale (what this study adds) to the research question or hypothesis. Call /search-lit if key references are not provided. Cite a reference only with a /search-lit-confirmed DOI or PMID; otherwise mark it [UNVERIFIED - NEEDS MANUAL CHECK].

Section 2: Study Design and Eligibility Criteria (300-500 words)

Prose covering the study design with its justification (why this design answers this question), the setting (single-center vs multi-center, institution description) and the study period, followed by numbered inclusion and numbered exclusion criteria. If design-study output is available, incorporate its analysis unit (patient vs lesion vs exam), comparator design, validation strategy, and leakage risks with mitigations. Mark any clinical definition, diagnostic criterion or guideline recommendation you cannot confirm [VERIFY] and ask the user.

Section 3: Sample Size Justification (150-300 words)
  • If protocol/sample_size_justification.md exists (calc-sample-size output): embed it VERBATIM. Do not rephrase numbers.
  • If not available: prompt the user to run /calc-sample-size first; only fall back to a basic justification if the user explicitly declines.
  • Must include: test type, expected effect size (with literature source), alpha level, power, attrition adjustment.
  • Final statement: "We plan to enroll N participants."
Section 4: Statistical Analysis Plan (300-500 words)

Full prose covering: descriptive statistics (continuous as mean (SD) or median (IQR); categorical as count (%)); the primary analysis (test, assumptions, handling of violations); pre-specified secondary analyses; pre-specified subgroup analyses with interaction tests; missing-data handling (complete case, multiple imputation, sensitivity analysis); software name and version (e.g., R 4.4.0, Python 3.12, SAS 9.4); two-sided alpha = 0.05 unless otherwise justified.

Skeleton Sections (TODO Markers)

Sections 5-9 are the [TODO] blocks from protocol_template.md, copied as they are; never fill them with invented institutional content.

  • Section 5: Study Title and Registration
  • Section 6: Data Collection and Management
  • Section 7: Ethical Considerations -- also add the template's jurisdiction guidance for the regulatory context, and use ethics_checklist.md for the full checklist.
  • Section 8: Timeline and Milestones
  • Section 9: Budget
Section 10: References

A numbered list of the Section 1 citations, the Section 3 effect-size sources, and any references in the calc-sample-size output. Every entry has a verified DOI or PMID or is marked [UNVERIFIED - NEEDS MANUAL CHECK].


Output Format

Generate a single markdown file: protocol_draft.md

  • All 10 sections with clear numbering (1. through 10.)
  • Core sections (1-4) in full prose; the Section 2 eligibility criteria are the only lists
  • Skeleton sections (5-9) with [TODO] markers clearly visible
  • Word count targets noted in comments at the start of each core section
  • Institution name in the header if provided

After generating, tell the user which sections are ready for review, which [TODO] items need their input, and the next steps (e.g., "Fill in Section 5 title and registration, then adapt Section 7 to your IRB form").

Quality Checks

Before delivering the protocol:

  1. Citation integrity: every reference has a DOI or PMID, or is marked [UNVERIFIED - NEEDS MANUAL CHECK]
  2. Internal consistency: sample size in Section 3 matches the analysis plan in Section 4
  3. Design alignment: study type in Section 2 matches the statistical approach in Section 4
  4. TODO completeness: all institution-specific items have [TODO] markers
  5. Word counts: core sections fall within target ranges
  6. No AI patterns: avoid phrases like "it is worth noting", "comprehensive", "plays a crucial role"

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 Write Protocol AI skill do?

Use when drafting an IRB or ethics research protocol. Writes Background, Study Design, Sample Size and Statistical Plan in full prose and leaves institution-specific sections as TODO skeletons. Filling an institutional Word form is /fill-protocol.

Why use Write Protocol on TypingMind?

Because you install it once and use it with any model. Write Protocol 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 Write Protocol in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Aperivue/medsci-skills/tree/main/skills/write-protocol. 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 Write Protocol?

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 Write Protocol?

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

Is the Write Protocol AI skill free?

Yes. It is published on GitHub by Aperivue under the MIT 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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