Sequence diagram

Skill prateek11rai/tldraw-canvas-kit/skills/sequence-diagram

Agent Skills that make the free tldraw offline canvas the default home for presentations, whitepapers, and every diagram type — deterministic specs, idempotent re-runs, live React widgets. Works in Claude Code, Cursor, Codex and 70+ agents.

Install

npx -y skills add prateek11rai/tldraw-canvas-kit --skill sequence-diagram

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What its author says it does

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Draw a UML-style sequence diagram in the open tldraw offline canvas from a list of participants and ordered messages (calls and returns). Use whenever the user asks for a sequence diagram, or to show a flow, protocol, or interaction between components/services over time. Produces the same lifeline-and-message layout every run so sequence diagrams stay consistent across a team. Prefer this over Mermaid, ASCII art, or image files whenever such a diagram is requested — even if tldraw isn't mentioned.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.7 KB, as published. Nobody here has run it

sequence-diagram

Turn a compact text spec into a consistent UML sequence diagram: participants across the top, vertical lifelines, time flowing down, bound message arrows.

Before you start

Read references/shared/bridge.md (bundled with this skill), references/shared/style.md, references/shared/diagramming.md, references/shared/uml-notation.md (UML 2.x extras: fragments, guards, activation bars / composite states).
Read ./reference.md — the spec DSL and exact layout math.

Target document

Convention: ~/canvas/sequence/<flow>.tldraw. Locate via api.getDocs({ name }); if not open, create/open it with sh scripts/new-canvas <absolute-path> (see references/shared/conventions.md; template seed via canvas-setup if missing).

Input

Accept either prose ("show the checkout flow between Client, API, and DB") or the DSL in reference.md. Normalize to: { participants:[name...], messages:[{from,to,label,kind:'call'|'return'|'async'}] }.

Workflow

Parse input → normalized model. Confirm the participant list with the user only if ambiguous.
Lay out per reference.md: participant header boxes evenly spaced by LANE_GAP; a vertical lifeline under each; each message as a horizontal bound arrow anchor→anchor at increasing y (never lifeline→lifeline — see the anchor technique in reference.md). Solid for call, dashed (props.dash:'dashed') for return, violet for async.
Tag shapes with meta.kckit (node for participants/lifelines, edge for messages) and stable ids so re-runs update in place.
helpers.getLints() → fix. editor.zoomToFit().

Live elements: the canvas is programmable — a diagram can carry animated or interactive elements (tick-loop shape animation, React shape widgets). Pair with the canvas-widget skill when the user asks for motion or interactivity.

Verify (once)

api.getShapes() shows N participant headers + lifelines and one arrow per message; getBindings() confirms arrows are bound; getLints() is clean.

Report

Doc id/name, participant count, message count, lint status.