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Figshare Skill

Community
Agents365-ai
figshare-skill

Use whenever the user wants to interact with Figshare - searching public datasets/articles, downloading Figshare files, listing their own articles/collections/projects, creating or updating articles, or uploading files (including large multi-part uploads) via the Figshare v2 REST API. Trigger on mentions of "figshare", figshare DOIs (10.6084/m9.figshare.*), figshare.com URLs, or phrases like "upload my dataset to figshare", "publish to figshare", "get figshare article".

Overview

PublisherAgents365-ai
Repository365-skills
Skill namefigshare-skill
Stars
99
Forks
16
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by Agents365-ai on GitHub. Read the source before you install it.

Installation

Install the Figshare Skill 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/Agents365-ai/365-skills/tree/main/plugins/figshare/skills/figshare-skill
  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/Agents365-ai/365-skills.git /tmp/365-skills
mkdir -p .claude/skills
cp -r /tmp/365-skills/plugins/figshare/skills/figshare-skill .claude/skills/figshare-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Figshare Skill 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 Figshare Skill 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 Figshare Skill 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.

Figshare Skill

Interact with the Figshare v2 REST API to search, download, create, and upload research outputs.

Prerequisites

  • curl and jq available on PATH.

  • For authenticated endpoints (anything under /account/... or uploads), a personal token from https://figshare.com/account/applications exported as:

    bash
    export FIGSHARE_TOKEN=xxxxxxxxxxxxxxxx
  • Public endpoints (search, public articles, downloads) need no token.

Always confirm with the user before creating, modifying, publishing, or deleting anything on their account — these are hard to reverse.

Update check

Throttle to one check per 24 hours per installation; never mutate the skill directory without explicit user consent.

  1. If <this-skill-dir>/.last_update exists and is less than 24 hours old, skip this step entirely.

  2. Otherwise, fetch the latest tag from upstream:

    bash
    git -C <this-skill-dir> ls-remote --tags origin 'v*' 2>/dev/null \
      | awk '{print $2}' | sed 's|refs/tags/||' \
      | sort -V | tail -1
  3. Compare with this skill's metadata.version from the frontmatter. If the upstream tag is strictly newer (semver), tell the user one line and ask:

    "A newer version of this skill is available: vX.Y.Z → vA.B.C. Want me to git pull?"

    If they say yes, run git -C <this-skill-dir> pull --ff-only. Refresh .last_update either way so the prompt doesn't repeat for 24 hours.

  4. If upstream is the same or older, refresh .last_update silently and continue.

  5. On any failure (offline, not a git checkout — e.g. ClawHub-installed copy, read-only path, no permission), swallow the error silently and continue with the user's task. Do not mention the failure.

API Basics

  • Base URL: https://api.figshare.com/v2
  • Auth header: Authorization: token $FIGSHARE_TOKEN
  • Content-Type: application/json for POST/PUT bodies
  • Rate limit: keep it under ~1 request/second to avoid abuse throttling
  • Errors: JSON body with message, code; common codes 400/401/403/404/422

Common Recipes

Search public articles

bash
curl -s -X POST https://api.figshare.com/v2/articles/search \
  -H "Content-Type: application/json" \
  -d '{"search_for": ":title: single cell", "page_size": 20}' | jq

Field operators: :title:, :author:, :tag:, :category:, :doi:, :resource_doi:.

Get a public article (by ID or DOI)

bash
curl -s https://api.figshare.com/v2/articles/{article_id} | jq
# or resolve from a figshare.com URL: the numeric tail is the article_id

Download all files from a public article

bash
ART=12345678
curl -s https://api.figshare.com/v2/articles/$ART/files \
  | jq -r '.[] | "\(.download_url)\t\(.name)"' \
  | while IFS=$'\t' read -r url name; do curl -L -o "$name" "$url"; done

List your own articles

bash
curl -s -H "Authorization: token $FIGSHARE_TOKEN" \
  "https://api.figshare.com/v2/account/articles?page=1&page_size=50" | jq

Create an article (draft)

bash
curl -s -X POST https://api.figshare.com/v2/account/articles \
  -H "Authorization: token $FIGSHARE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "title": "My dataset",
    "description": "Full description here.",
    "defined_type": "dataset",
    "tags": ["demo"],
    "categories": [2]
  }' | jq

Response is { "location": ".../account/articles/{id}", "entity_id": 123 }.

Update / publish an article

bash
# update metadata
curl -s -X PUT https://api.figshare.com/v2/account/articles/$ART \
  -H "Authorization: token $FIGSHARE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"title": "New title"}'

# publish (becomes public, assigns DOI, version is frozen)
curl -s -X POST https://api.figshare.com/v2/account/articles/$ART/publish \
  -H "Authorization: token $FIGSHARE_TOKEN"

Always ask before publishing — it's permanent for that version.

Collections & projects

bash
# create collection that groups existing articles
curl -s -X POST https://api.figshare.com/v2/account/collections \
  -H "Authorization: token $FIGSHARE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"title": "My Collection", "articles": [123, 456]}'

# create project
curl -s -X POST https://api.figshare.com/v2/account/projects \
  -H "Authorization: token $FIGSHARE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"title": "Research Project"}'

Uploading Files (Multi-part Flow)

Figshare uploads are 3-step: initiate → PUT each part → complete. Use the bundled helpers for anything non-trivial:

bash
# upload a file to an existing draft article
./scripts/upload.sh <article_id> <path/to/file>

# batch-download every file from a public article (accepts id or figshare.com URL)
./scripts/download.sh <article_id_or_url> [output_dir]

# reserve + upload + publish a new version of an already-published article
./scripts/new-version.sh <article_id> <path/to/file>

The raw flow, in case you need to adapt it:

  1. Initiate — compute md5 + size, POST to article:

    bash
    SIZE=$(stat -f%z "$FILE" 2>/dev/null || stat -c%s "$FILE")
    MD5=$(md5sum "$FILE" | awk '{print $1}')   # or: md5 -q on macOS
    curl -s -X POST https://api.figshare.com/v2/account/articles/$ART/files \
      -H "Authorization: token $FIGSHARE_TOKEN" \
      -H "Content-Type: application/json" \
      -d "{\"md5\":\"$MD5\",\"name\":\"$(basename $FILE)\",\"size\":$SIZE}"

    Response has location pointing at /account/articles/$ART/files/$FILE_ID.

  2. Fetch upload info from that file record — it contains an upload_url. GET the upload_url to learn the part layout (parts: [{partNo, startOffset, endOffset}]).

  3. Upload parts — for each part, PUT the byte range to ${upload_url}/${partNo}:

    bash
    dd if="$FILE" bs=1 skip=$START count=$((END-START+1)) 2>/dev/null \
      | curl -s -X PUT --data-binary @- "${upload_url}/${partNo}" \
        -H "Authorization: token $FIGSHARE_TOKEN"
  4. Complete — POST to the file record to finalize:

    bash
    curl -s -X POST https://api.figshare.com/v2/account/articles/$ART/files/$FILE_ID \
      -H "Authorization: token $FIGSHARE_TOKEN"

Why three steps: Figshare streams large files through a separate upload service. Skipping the complete call leaves the file in a pending state and it won't appear on the article.

Pagination

Most list endpoints accept either page+page_size or limit+offset. Max page_size is typically 1000. For large harvests, loop until an empty page:

bash
page=1
while :; do
  out=$(curl -s "https://api.figshare.com/v2/articles?page=$page&page_size=100")
  [ "$(echo "$out" | jq 'length')" = "0" ] && break
  echo "$out" | jq -c '.[]'
  page=$((page+1))
  sleep 1
done

Troubleshooting

  • 401 — token missing/expired; re-check $FIGSHARE_TOKEN.
  • 403 on /account/... — token lacks the needed scope; regenerate with full permissions.
  • 422 on article create — missing required field (usually title) or bad categories/defined_type.
  • Upload parts mismatch — md5 or size in step 1 didn't match the bytes actually uploaded; recompute and restart.
  • Published article won't update — publishing freezes a version; create a new version instead.

References

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 Figshare Skill AI skill do?

Use whenever the user wants to interact with Figshare - searching public datasets/articles, downloading Figshare files, listing their own articles/collections/projects, creating or updating articles, or uploading files (including large multi-part uploads) via the Figshare v2 REST API. Trigger on mentions of "figshare", figshare DOIs (10.6084/m9.figshare.*), figshare.com URLs, or phrases like "upload my dataset to figshare", "publish to figshare", "get figshare article".

Why use Figshare Skill on TypingMind?

Because you install it once and use it with any model. Figshare Skill 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 Figshare Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Agents365-ai/365-skills/tree/main/plugins/figshare/skills/figshare-skill. 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 Figshare Skill?

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 Figshare Skill?

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

Is the Figshare Skill AI skill free?

Yes. It is published on GitHub by Agents365-ai 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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