Agent skill

Protocol Standardization

by aipoch in aipoch/medical-research-skills

Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be…

MITAuto-check passedResearch & Science

Install Protocol Standardization

skills CLI
$ npx skills add aipoch/medical-research-skills --skill protocol-standardization -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills protocol-standardization --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Protocol Design/protocol-standardization' .claude/skills/protocol-standardization && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
protocol-standardization
GitHub stars
2k
Token cost
~2.2k tokens
SKILL.md length
1,030 words
Files
5 (incl. references, assets)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be…

  • Works in 4 steps: Add acetone to lysate, mix. → Put at cold temperature for a while. → Spin down, remove supernatant. → …
  • Tasks that involve Operations and SOPs
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Protocol Standardization is an agent skill from aipoch/medical-research-skills. Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be explicitly marked as "To be supplemented/Not provided".

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files and assets (for example `POLISH_CHANGELOG.md`, `assets/protocol_template.md` and `eval_report_protocol-standardization_result.json`).

It sits in Research & Science, covering Operations and SOPs and Reproducible research. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Tasks that involve Operations and SOPs
  • Tasks that involve Reproducible research

Example prompts

  • “To be supplemented/Not provided”
  • “/protocol-standardization”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Add acetone to lysate, mix.
  2. Put at cold temperature for a while.
  3. Spin down, remove supernatant.
  4. Dry pellet, then resuspend.

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Protocol Standardization loads about 2.2k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 69 tokens; SKILL.md has 1,030 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,030 words, ~2,207 tokens.

Download SKILL.mdSave it as .claude/skills/protocol-standardization/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
protocol-standardization
description
Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be explicitly marked as "To be supplemented/Not provided".
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

  • You have messy notes (chat logs, notebook fragments, bullet points) and need a formal, reproducible experimental protocol.
  • You are preparing a lab SOP for standardization across multiple operators or sites.
  • You need to convert exploratory/iterative experimental steps into a structured method for documentation or publication support.
  • You are onboarding new team members and must clarify steps, parameters, and checkpoints without inventing missing information.
  • You are auditing an existing method to identify missing critical parameters and quality-control points.

Key Features

  • Converts fragmented experimental steps into a standardized protocol structure (prep → execution → closing).
  • Enforces parameter completeness for reproducibility (e.g., temperature, time, concentration, volume, mixing/rotation speed).
  • Prohibits fabrication: any unknown or uncertain information is explicitly labeled as "To be supplemented/Not provided".
  • Unifies units, terminology, and step formatting for consistency.
  • Adds operational checks: logical order, safety notes, and waste disposal requirements.
  • Supports structured output using reusable templates (see assets/protocol_template.md).
  • Provides format guidance and checklists via references/guide.md.

Dependencies

  • None (documentation-only skill; no runtime dependencies specified).

Example Usage

Input (raw experimental notes)

Goal: Protein precipitation and cleanup (example)

Materials/Reagents

  • Sample lysate: 200 µL
  • Acetone (pre-chilled): volume not recorded
  • Microcentrifuge tubes
  • Centrifuge

Steps (as recorded)

  1. Add acetone to lysate, mix.
  2. Put at cold temperature for a while.
  3. Spin down, remove supernatant.
  4. Dry pellet, then resuspend.
Output (standardized protocol)

Title: Protein Precipitation by Cold Acetone (Standardized Protocol)

Purpose

  • Precipitate proteins from lysate for downstream analysis.

Materials/Reagents

  • Sample lysate: 200 µL
  • Acetone (pre-chilled): To be supplemented/Not provided (final ratio/volume)
  • Microcentrifuge tubes
  • Centrifuge (model/rotor: To be supplemented/Not provided)

Equipment

  • Microcentrifuge capable of: To be supplemented/Not provided (×g or rpm)
  • Temperature control (ice bath / 4°C fridge / cold room): To be supplemented/Not provided

Procedure

A. Preparation

  1. Label microcentrifuge tubes with sample IDs.
  2. Pre-chill acetone to To be supplemented/Not provided (e.g., -20°C) and prepare a cold incubation environment (To be supplemented/Not provided).

B. Execution 3. Add pre-chilled acetone to 200 µL lysate at a ratio of To be supplemented/Not provided (e.g., 4:1 acetone:lysate). 4. Mix by To be supplemented/Not provided (vortex/inversion) for To be supplemented/Not provided (time). 5. Incubate at To be supplemented/Not provided (temperature) for To be supplemented/Not provided (time). 6. Centrifuge at To be supplemented/Not provided (×g or rpm) for To be supplemented/Not provided (time) at To be supplemented/Not provided (temperature). 7. Carefully remove and discard the supernatant without disturbing the pellet.

C. Closing 8. Air-dry pellet for To be supplemented/Not provided (time) until residual solvent is removed (do not overdry if resuspension is required). 9. Resuspend pellet in To be supplemented/Not provided (buffer type and volume) by To be supplemented/Not provided (pipetting/vortexing) for To be supplemented/Not provided (time).

Critical Parameters to Supplement

  • Acetone:lysate ratio (or acetone volume)
  • Incubation temperature and duration
  • Centrifugation force/time/temperature
  • Pellet drying time
  • Resuspension buffer and volume

Quality Control / Checkpoints

  • Pellet presence after centrifugation: Expected (yes/no criteria to be supplemented)
  • Supernatant clarity: To be supplemented/Not provided
  • Resuspension completeness: To be supplemented/Not provided

Safety & Waste Disposal

  • Acetone handling: To be supplemented/Not provided (PPE/ventilation requirements)
  • Solvent waste disposal route: To be supplemented/Not provided

Suggested Output Location

  • outputs/ProteinPrecipitation_Acetone.txt (example naming)

Implementation Details

  • Workflow Structure

    1. Step Review: Collect all steps/materials; classify into preparation, execution, and closing phases.
    2. Parameter Completion: Identify required parameters (time, temperature, concentration, volume, mixing/rotation speed, centrifugation force, etc.).
      • If missing/uncertain, do not infer; mark as "To be supplemented/Not provided" and list fields requiring supplementation.
    3. Standardization and Organization: Rewrite into a consistent protocol format; unify units and terminology.
    4. Output Check: Validate logical sequence and operability; add safety and waste disposal notes.
  • Parameter Rules

    • Never fabricate values.
    • Use consistent units (e.g., °C, min, mL/µL, mM, ×g or rpm).
    • Explicitly surface “critical control points” (steps where parameter deviations affect outcomes).
  • Templates and References

    • Protocol template: assets/protocol_template.md
    • Output formats, checklists, and key checkpoints: references/guide.md
  • Output Path and Naming

    • Default output directory: outputs/
    • Naming convention: {Experiment_Info_Abbreviation}.txt
Show full SKILL.md (392 more words)Show less

When Not to Use

  • Do not proceed when required input files, identifiers, parameters, or context are missing — ask the user to provide them first.
  • Do not assume capabilities beyond this skill's declared scope when the user requests external operations or inferences.
  • Do not proceed without user confirmation when overwriting existing results, executing high-cost batch operations, or expanding task scope.

Required Inputs

FieldRequiredFormat/SourceExampleIf Missing
User task descriptionYesTextResearch question, writing goal, analysis objectiveStop and ask user to provide
Primary input materialDepends on taskText, file path, ID, table, or literaturePMID, PDF, CSV, DOCX, keywords, etc.Specify which material type is missing
Output preferenceNoTextLanguage, format, target journal, templateUse skill default format

Output Contract

  • Primary output: Structured result or target file aligned with this skill's objective.
  • Optional output: Intermediate check notes, issue list, supplementary suggestions, or generated file paths.
  • Format requirement: Unless the user specifies otherwise, prefer stable, reviewable Markdown or JSON; if the skill's bundled script requires a fixed format, use that format.
  • If partially complete: Must explicitly mark as PARTIAL and state which steps are completed and which remain.

Failure Handling

  • Missing critical input: Explicitly state which fields, files, or identifiers are missing and pause.
  • Script, template, or resource execution failure: Report the failing step, likely cause, and recovery suggestions — do not silently degrade.
  • Partial completion only: Return the verified portion first, then list remaining blockers and suggested next steps.

User Checkpoints

  • Before executing batch processing, overwriting files, long-running searches, or multi-stage generation, confirm scope and output format with the user.
  • Before proceeding when a key judgment is ambiguous, evidence is insufficient, or the workflow is entering the next stage, confirm with the user.

Input Validation

This skill accepts requests that match the documented purpose of protocol-standardization and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

protocol-standardization only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Quick Validation

  • Check that key scripts, templates, or reference file paths this skill depends on exist.
  • Check that the final output contains the core fields, sections, or files specified for this task.
  • Check that results clearly mark assumptions, limitations, and incomplete items.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references, assets) in scientific-skills/Protocol Design/protocol-standardization of aipoch/medical-research-skills.

  • SKILL.md
  • POLISH_CHANGELOG.md
  • assets/protocol_template.md
  • eval_report_protocol-standardization_result.json
  • references/guide.md

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Protocol Standardization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Protocol Standardization compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Protocol Standardization this skillaipoch/medical-research-skills2k—~2.2kAutomated safety check: PassMIT
Radiology Experiment Designhuang-sir1/radiology-skills1.9k—~3.6kAutomated safety check: PassCustom licence
Taipei Permit Drawing Standardsh30190/HJPLUS_Taiwan_Architect_KB157—~4.6kAutomated safety check: PassCC-BY-SA-4.0
Jqte Io Cgefranklee16/academic-research-skills2231 repos~419Automated safety check: PassNone
Peer ReviewK-Dense-AI/claude-scientific-writer2.4k2 repos~3.1kAutomated safety check: NotesMIT
CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw6171 repos~1.8kAutomated safety check: PassNone

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Questions about Protocol Standardization

What does Protocol Standardization do?

Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be…. Protocol Standardization is an agent skill from aipoch/medical-research-skills. Standardize fragmented experimental steps into reproducible protocol documents when you need method organization, lab SOP drafting, or cross-operator reproducibility; missing parameters must be explicitly marked as "To be supplemented/Not provided".

When should I use Protocol Standardization?

Protocol Standardization fits situations like: tasks that involve Operations and SOPs; tasks that involve Reproducible research.

How do I install Protocol Standardization in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill protocol-standardization -a claude-code`. Or copy the skill folder (scientific-skills/Protocol Design/protocol-standardization in aipoch/medical-research-skills) into .claude/skills/protocol-standardization in your project. Claude Code loads it when a task matches its description.

How do I install Protocol Standardization in Codex?

Run `npx skills add aipoch/medical-research-skills --skill protocol-standardization -a codex`. Or copy the skill folder (scientific-skills/Protocol Design/protocol-standardization in aipoch/medical-research-skills) into .agents/skills/protocol-standardization in your project. Codex loads it when a task matches its description.

Can I use Protocol Standardization in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill protocol-standardization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/protocol-standardization, .gemini/skills/protocol-standardization, .github/skills/protocol-standardization and .opencode/skills/protocol-standardization in your project.

What does Protocol Standardization need to run?

SKILL.md names no scripts, command-line tools or credentials: Protocol Standardization is instructions for the agent only.

Does Protocol Standardization access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Protocol Standardization safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Protocol Standardization use?

Protocol Standardization is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Protocol Standardization use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 156 tokens, read only when the agent opens those files.

What are the alternatives to Protocol Standardization?

Skills that share tags, products or a category with Protocol Standardization: Radiology Experiment Design (huang-sir1/radiology-skills, 1.9k stars), Taipei Permit Drawing Standards (h30190/HJPLUS_Taiwan_Architect_KB, 157 stars), Jqte Io Cge (franklee16/academic-research-skills, 223 stars) and Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Protocol Standardization?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,973 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.