Agent skill

Labarchive Integration

by aipoch in aipoch/medical-research-skills

Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility…

MITAuto-check passedResearch & Science

Install Labarchive Integration

skills CLI
$ npx skills add aipoch/medical-research-skills --skill labarchive-integration -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills labarchive-integration --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/Academic Writing/labarchive-integration' .claude/skills/labarchive-integration && 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
labarchive-integration
GitHub stars
2k
Token cost
~1.7k tokens
SKILL.md length
769 words
Files
9 (incl. scripts, references, assets)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility…

  • Works in 5 steps: Validate authorization and source… → Choose the acquisition path → Normalize notebook evidence → …
  • Tasks that involve Scientific writing
  • SKILL.md covers When to Use, When Not to Use, Primary Writing Outputs and Authorized Input Sources, plus 8 more sections
  • Runs Python scripts from its folder; calls python

What it does

Labarchive Integration is an agent skill from aipoch/medical-research-skills. Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts, reference files and assets (for example `assets/writing_outputs_template.md`, `labarchive-integration_audit_result_v1.json` and `references/api_reference.md`).

It sits in Research & Science, covering Scientific writing 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 Scientific writing
  • Tasks that involve Reproducible research

Example prompts

  • “Use the labarchive-integration skill to convert LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic…”
  • “/labarchive-integration”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Validate authorization and source sufficiency
  2. Choose the acquisition path
  3. Normalize notebook evidence
  4. Draft the requested academic writing output
  5. Run the final writing safety pass

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

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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

Labarchive Integration loads about 1.7k tokens when it runs, and up to ~9.9k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 769 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.9k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 769 words, ~1,740 tokens.

Download SKILL.mdSave it as .claude/skills/labarchive-integration/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
labarchive-integration
description
Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
license
MIT
author
AIPOCH

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

LabArchives Integration

This skill is an Academic Writing workflow built around LabArchives evidence. Its goal is not just API access, but turning authorized ELN material into manuscript-ready writing deliverables.

When to Use

  • The user has LabArchives notebook content and needs a Methods draft grounded in recorded procedures.
  • The user needs a data availability statement, reproducibility appendix, experiment timeline, or submission support summary based on ELN records.
  • The user wants to gather authorized notebook data first, then convert it into academic writing outputs.
  • The user needs a deterministic evidence-to-writing workflow instead of freeform summarization.

When Not to Use

  • The user asks for unauthorized access to notebooks or other users' data.
  • The user wants clinical recommendations, diagnosis, or treatment language.
  • The user asks you to fabricate notebook records, timestamps, protocol details, or compliance statements that are not present in the source.
  • The user has no authorized export, no notebook metadata, and no textual record to ground the writing output.

Primary Writing Outputs

This skill supports these deliverables:

  • Methods Draft Based on notebook entries, protocols, instrument logs, and sample-processing notes
  • Data Availability Statement Based on notebook identifiers, repository links, export status, and sharing constraints
  • Reproducibility Appendix Based on protocol versions, software environments, parameter logs, and file provenance
  • Experiment Timeline Summary Based on dated entries, milestones, and decision points
  • Submission Support Note Based on notebook scope, audit trail, and documentation completeness

Authorized Input Sources

Use one or more of:

  • exported notebook text or JSON
  • manually pasted LabArchives entry content
  • protocol summaries
  • experiment metadata tables
  • authorized backup output from bundled scripts

Optional collection step:

  • scripts/setup_config.py
  • scripts/notebook_operations.py
  • scripts/entry_operations.py

Writing Output Contract

Output A: Methods Draft

Must include:

  • study material or sample context
  • experimental workflow in chronological order
  • instrument / assay / software mentions if present in source
  • quality-control or versioning note if present in source
  • no invented parameter values
Output B: Data Availability Statement

Must include:

  • what data are available
  • where they are stored or how they can be requested
  • any access restrictions
  • relationship to LabArchives or downstream repository
Output C: Reproducibility Appendix

Must include:

  • protocol version references
  • software or pipeline identifiers if present
  • provenance or notebook traceability note
  • missing-record warning if the audit trail is incomplete
Output D: Experiment Timeline Summary

Must include:

  • dated milestone order
  • major protocol transitions
  • validation / repeat / deviation points if documented

Workflow

1. Validate authorization and source sufficiency

Confirm:

  • the requester has authorized access to the notebook data
  • the source contains enough grounded information for the requested writing output

If not, stop and use the refusal template in ## Refusal and Recovery Contract.

2. Choose the acquisition path

Use direct source text if already available. Prefer this path for speed.

If data must be collected first, use one of the bundled scripts:

bash
python scripts/setup_config.py
python scripts/notebook_operations.py --help
python scripts/entry_operations.py --help

Use --dry-run where available before live execution.

Show full SKILL.md (312 more words)Show less
3. Normalize notebook evidence

Extract only writing-relevant elements:

  • dates
  • protocol names and versions
  • sample or cohort descriptors
  • software / pipeline names
  • QC notes
  • repository / export details
  • compliance or sharing constraints
4. Draft the requested academic writing output

Keep the prose:

  • factual
  • audit-trail grounded
  • publication appropriate
  • free of operational noise that does not belong in the manuscript deliverable
5. Run the final writing safety pass

Check that:

  • every claim maps back to source evidence
  • missing evidence is labeled as missing
  • no compliance statement is invented
  • no unauthorized identifiers are surfaced

Refusal and Recovery Contract

If the workflow cannot proceed safely, respond with:

text
Cannot generate the requested LabArchives-based writing output yet.
Reason: <missing authorization / insufficient export / incomplete metadata / unsupported request>
Minimum next step:
- <step 1>
- <step 2>

Use this contract for:

  • missing notebook authorization
  • no usable export or pasted content
  • requests to infer missing protocol details
  • requests to expose restricted data

Script Usage Notes

The bundled scripts are supporting collection utilities, not the final output themselves.

  • setup_config.py: create or validate configuration
  • notebook_operations.py: list notebooks, plan backups, or perform authorized exports
  • entry_operations.py: inspect entry-level content or upload artifacts when explicitly needed

If a script path fails:

  • report the exact command
  • report the exact failure
  • continue with direct writing only if enough grounded notebook text is already available

Academic Writing Style Rules

  • write in neutral, methods-oriented academic prose
  • prefer verifiable chronology over interpretive narrative
  • do not overclaim documentation quality if the notebook trail is partial
  • clearly distinguish documented, not documented, and not provided

Use assets/writing_outputs_template.md as the default skeleton for the four main writing deliverables.

Deterministic Rules

  • keep output headings stable
  • do not expose raw credentials, tokens, or private notebook identifiers unless the user explicitly needs authorized internal formatting
  • if a timestamp or version is missing, say it is not documented
  • treat data availability and reproducibility statements as formal manuscript components, not casual notes

Completion Checklist

  • Authorization boundary checked
  • Source sufficiency checked
  • Requested writing deliverable selected explicitly
  • All statements grounded in notebook evidence
  • Missing evidence labeled rather than invented

© 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 8 other files (scripts, references, assets) in scientific-skills/Academic Writing/labarchive-integration of aipoch/medical-research-skills.

  • SKILL.md
  • assets/writing_outputs_template.md
  • labarchive-integration_audit_result_v1.json
  • references/api_reference.md
  • references/authentication_guide.md
  • references/integrations.md
  • scripts/entry_operations.py
  • scripts/notebook_operations.py
  • scripts/setup_config.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Labarchive Integration 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.

Labarchive Integration compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Labarchive Integration this skillaipoch/medical-research-skills2k—~1.7kAutomated safety check: PassMIT
Modeling Code and Result Contractsyushui2022/MathModel-Skill452—~1.4kAutomated safety check: PassMIT
Backward Traceabilitylingzhi227/agent-research-skills384—~802Automated safety check: PassNone
Meta-model-agent Math Modeling PipelineWuXinbo-bo/Math-model-skills111—~2.3kAutomated safety check: PassMIT
Nature Data AvailabilityYuan1z0825/nature-skills46k—~957Automated safety check: PassApache-2.0
Paper Pipeline Assemblylingzhi227/agent-research-skills384—~971Automated safety check: PassNone

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Questions about Labarchive Integration

What does Labarchive Integration do?

Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility…. Labarchive Integration is an agent skill from aipoch/medical-research-skills. Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes.

When should I use Labarchive Integration?

Labarchive Integration fits situations like: tasks that involve Scientific writing; tasks that involve Reproducible research.

How do I install Labarchive Integration in Claude Code?

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

How do I install Labarchive Integration in Codex?

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

Can I use Labarchive Integration 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 labarchive-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/labarchive-integration, .gemini/skills/labarchive-integration, .github/skills/labarchive-integration and .opencode/skills/labarchive-integration in your project.

What does Labarchive Integration need to run?

Going by SKILL.md and its folder, Labarchive Integration needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Labarchive Integration 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 Labarchive Integration 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Labarchive Integration use?

Labarchive Integration 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 Labarchive Integration use?

About 1.7k tokens (SKILL.md is roughly 7k 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 8.2k tokens, read only when the agent opens those files.

What are the alternatives to Labarchive Integration?

Skills that share tags, products or a category with Labarchive Integration: Modeling Code and Result Contracts (yushui2022/MathModel-Skill, 452 stars), Backward Traceability (lingzhi227/agent-research-skills, 384 stars), Meta-model-agent Math Modeling Pipeline (WuXinbo-bo/Math-model-skills, 111 stars) and Nature Data Availability (Yuan1z0825/nature-skills, 46k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Labarchive Integration?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 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.