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Figure Gallery

By Dsadd4· Dsadd4/AgentFigureGallery· 0

Query scientific figures, select visual examples, and export reference bundles for plotting.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.
    Install
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    This copies the whole skill folder into ~/.claude/skills/agent-figure-gallery-dsadd4/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
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  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Query visual scientific figure references, show candidates for human preference selection, export selected reference bundles, and guide plotting agents from human-selected visual examples to code action.

What this skill does

Agent Figure Gallery

Core Rule

Treat this skill as a lightweight controller. Do not load the full visual corpus into the skill. Use AGENT_FIGURE_GALLERY_ROOT or DRAWING_KB_ROOT to point at the external AgentFigureGallery knowledge base.

Key Files

  • KB root: AGENT_FIGURE_GALLERY_ROOT=/path/to/AgentFigureGallery
  • CLI: agentfiguregallery or python -m agentfiguregallery.cli
  • Gallery server: backend command that serves the reference gallery on localhost
  • Candidate index: data/reference_candidate_index.json
  • Global preferences: data/reference_global_preferences.json
  • Reference sessions: outputs/reference_sessions/

Minimal Workflow

  1. Resolve the KB root: 
    export AGENT_FIGURE_GALLERY_ROOT=/path/to/AgentFigureGallery
  2. Query before reading individual references: 
    agentfiguregallery query --task "<user task>"
  3. Generate visible candidates: 
    agentfiguregallery gallery --plot-type <plot_type> --task "<user task>" --limit 50 --serve
  4. Record human preferences: 
    agentfiguregallery prefer --session outputs/reference_sessions/<session_id> --like <ID> --reject <ID> --select <ID>
  5. Export a selected bundle: 
    agentfiguregallery bundle --session outputs/reference_sessions/<session_id> --copy-scripts
  6. Use the bundle before writing or revising plotting code.

Preference Semantics

  • like: useful for this task or plot type.
  • reject: not useful for this task or plot type.
  • select: use this candidate for the current agent action.
  • global_like: generally useful across tasks.
  • global_reject: hide from future sessions.

Local preferences must preserve plot_type. Global preferences are cross-task.

Validation

After changing the CLI, gallery, preference logic, or bundle export:

agentfiguregallery gallery --plot-type embedding_plot --limit 20 --serve
agentfiguregallery prefer --session outputs/reference_sessions/<session_id> --like E01 --select E02
agentfiguregallery bundle --session outputs/reference_sessions/<session_id>

Success means visible candidates render, stable IDs are shown, preferences persist, global rejects are hidden from later generated sessions, and the bundle contains selected references plus source code paths.

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