Bioconductor Gypsum logo

Bioconductor Gypsum

Organization
bioMate-AI
bioconductor-gypsum

Client for the gypsum REST API (https://gypsum.artifactdb.com), a cloud-based file store in the ArtifactDB ecosystem. This package provides functions for uploads, downloads, and various adminstrative and management tasks. Check out the docu

Overview

PublisherbioMate-AI
Repositorybiomate-bioconductor-kb
Skill namebioconductor-gypsum
Stars
804
Forks
66
Bundled files
Instructions only
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 bioMate-AI on GitHub. Read the source before you install it.

Installation

Install the Bioconductor Gypsum 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/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/general/gypsum
  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/bioMate-AI/biomate-bioconductor-kb.git /tmp/biomate-bioconductor-kb
mkdir -p .claude/skills
cp -r /tmp/biomate-bioconductor-kb/skills/general/gypsum .claude/skills/bioconductor-gypsum
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bioconductor Gypsum 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 Bioconductor Gypsum 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 Bioconductor Gypsum 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.

gypsum

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 1.8.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Depends: httr2, jsonlite, filelock, rappdirs
  • Imports: httr2, jsonlite, filelock, rappdirs
  • Install: BiocManager::install("gypsum")

When to Use

  • Programmatically downloading files, manifests, and summaries from the gypsum bucket using saveFile, saveVersion, fetchManifest, and fetchSummary.
  • Uploading files to the gypsum backend using the upload sequence: startUpload, uploadFiles, and completeUpload.
  • Creating new versions of existing assets efficiently by deduplicating redundant files using cloneVersion and prepareDirectoryUpload.
  • Validating metadata against the Bioconductor JSON schema prior to upload using validateMetadata.
  • Managing project permissions, probational uploads, and quotas using setPermissions, approveProbation, and setQuota.

When NOT to Use

  • For general-purpose cloud storage interactions (like raw Google Cloud Storage buckets) without an ArtifactDB backend, use packages like googleCloudStorageR instead.
  • For downloading standard Bioconductor package source files or annotation resources, use BiocManager or AnnotationHub instead.
  • For local-only file management and caching without a REST API backend, use BiocFileCache instead.

Data Requirements

  • Input format: File paths, directory structures, or metadata lists formatted according to the ArtifactDB JSON schema.
  • Authentication: Requires a GitHub OAuth token for write operations (uploads, deletions, permission changes), set via setAccessToken. Read operations are public.
  • Network: Requires an active internet connection to communicate with the gypsum REST API endpoint.

Key Parameters

  • project: Character; the name of the project on the gypsum server.
  • asset: Character; the specific asset within the project.
  • version: Character; the version string of the asset to upload or download.
  • directory: Character; local directory path containing files for upload in startUpload and uploadFiles.
  • destination: Character; local directory path where downloaded files should be saved in cloneVersion.
  • links: Data frame; used in startUpload to deduplicate redundant files on the backend by linking to existing files.

Best Practices

  • Wrap the upload sequence (uploadFiles, completeUpload) in a tryCatch block and call abortUpload in the error handler to clean up if the upload fails.
  • Use cloneVersion and prepareDirectoryUpload to expedite the creation of new asset versions by linking unmodified files to their counterparts in the previous version.
  • Always validate metadata using validateMetadata against the schema fetched by fetchMetadataSchema to ensure downstream databases can index the files.
  • Check the current usage of a project using fetchUsage and fetchQuota before initiating large uploads to ensure sufficient storage space.

Common Pitfalls

  • Unauthorized upload attempts: Attempting to upload or modify assets without setting a valid GitHub token will fail; fix this by authenticating using setAccessToken or prompting the user.
  • Modifying symlinks directly: When using cloneVersion, modifying a symlinked file directly will alter the linked source; fix this by deleting the symlink and replacing it with a new file before uploading.
  • Incomplete uploads: Failing to call completeUpload after uploadFiles leaves the upload in a pending state; ensure the full upload sequence is executed.

Alternatives

  • BiocFileCache: Best for managing local caches of remote files without a dedicated REST API backend.
  • AnnotationHub / ExperimentHub: The standard Bioconductor infrastructure for distributing curated annotation and experimental datasets.

Citations

  • Lun et al. (2024), "Interface to the gypsum REST API", Bioconductor Manual.

References


Run this on BioMate

This skill is the knowledge layer — when, why, and how to use gypsum. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open gypsum on BioMate →

Frequently asked questions

What does the Bioconductor Gypsum AI skill do?

Client for the gypsum REST API (https://gypsum.artifactdb.com), a cloud-based file store in the ArtifactDB ecosystem. This package provides functions for uploads, downloads, and various adminstrative and management tasks. Check out the docu

Why use Bioconductor Gypsum on TypingMind?

Because you install it once and use it with any model. Bioconductor Gypsum 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 Bioconductor Gypsum in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/general/gypsum. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bioconductor Gypsum?

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 Bioconductor Gypsum?

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

Is the Bioconductor Gypsum AI skill free?

It is published on GitHub by bioMate-AI. 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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