Tldraw

Tldraw

Deterministic read/write for tldraw canvases. The .tldr format is plain JSON ({tldrawFileFormatVersion: 1, schema, records}); Tools/Tldr.ts writes records that pass tldraw's own validator, so generated files open cleanly in the tldraw web editor, the VS Code tldraw extension, or the desktop app. Two directions: model → canvas (sketch diagrams) and canvas → model (read and structure a human's rough thinking).

Customization

Before executing, check for user customizations at: ~/.claude/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Tldraw/

If this directory exists, load and apply any PREFERENCES.md found there (default canvas directory, preferred colors/register, default open surface). If not, proceed with defaults.

Voice Notification

When executing a workflow, do BOTH:

1. Send voice notification:

   bashCopy code
   curl -s -X POST http://localhost:31337/notify \
     -H "Content-Type: application/json" \
     -d '{"message": "Running WORKFLOWNAME in Tldraw"}' \
     > /dev/null 2>&1 &
   

2. Output text notification:

   Copy code
   Running **WorkflowName** in **Tldraw**...
   

Workflow Routing

Quick Reference

• Tool: bun ~/.claude/skills/Tldraw/Tools/Tldr.ts <create|inspect|add|remove|move|settext|validate> <file.tldr> [flags]
• Record shapes, spec format, coordinate conventions: References/TldrFormat.md
• Vendored schema (tldraw 5.2.5): References/SchemaSnapshot.json

Examples

Example 1: Diagram for a post

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User: "Sketch the three-stage pipeline as a hand-drawn diagram"
→ Invokes SketchDiagram workflow
→ Writes spec JSON, runs Tldr.ts create + add, validates
→ Returns the .tldr path and how to open it; user nudges shapes and exports

Example 2: Organize an ideation canvas

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User: "I dumped ideas on my canvas — structure them"
→ Invokes StructureCanvas workflow
→ Tldr.ts inspect --json reads every shape's text and position
→ Clusters related items, adds frames + arrows, moves shapes into groups
→ User reopens the same file and sees the organized version

Gotchas

• zsh echo mangles spec JSON — it expands \n inside strings into real newlines, breaking JSON. Write the spec to a file (or use printf '%s') and pass --spec <file>; the tool also accepts --spec - on stdin, but only feed it from something that doesn't reinterpret escapes.
• Text is richText, never a plain string — labels on geo/text/note/arrow shapes are ProseMirror doc JSON ({"type":"doc","content":[{"type":"paragraph","content":[{"type":"text","text":"..."}]}]}). A bare string prop is rejected by tldraw's validator. Tldr.ts builds this for you; never hand-write a text prop.
• Arrow bindings require terminal: "start"|"end" — tldraw's own ArrowBindingUtil.getDefaultProps() omits it, but the schema validator rejects a binding without it (verified against tldraw 5.2.5). The tool sets it; if you hand-edit bindings, keep it.
• Raw records need every prop — records written to the file bypass editor defaulting, so a missing prop (e.g. growY on geo) fails validation on load. Always go through Tldr.ts add; don't append hand-rolled records.
• Fractional index strings order shapes — index values (a1, a2, …) are base62 lexicographic and must never end in 0. The tool generates them; duplicates cause z-order glitches in the editor.
• The desktop-app .tldraw format is a different thing — the tldraw desktop app's native save is a zip (sqlite + assets + scripts), not this JSON. This skill targets portable .tldr JSON, which the web editor, the VS Code extension, and the desktop app can all open/import.
• Editors hold files in memory — if the user has the canvas open while you edit it on disk, their surface may not reload (or may overwrite your change on save). Edit while closed, or tell the user to reopen after your write.

Opening a canvas

• VS Code / Cursor: the official tldraw extension opens .tldr files in-editor — fully local, right choice for private content.
• tldraw.com: File → Open. Content goes to a third-party web app — only for content already public-destined.
• Export to image: from any tldraw surface, select all → Export as SVG/PNG. (No headless export path ships with this skill.)

Execution Log

After completing any workflow, append a single JSONL entry:

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echo '{"ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","skill":"Tldraw","workflow":"WORKFLOW_USED","input":"8_WORD_SUMMARY","status":"ok|error","duration_s":SECONDS}' >> ~/.claude/LIFEOS/MEMORY/SKILLS/execution.jsonl