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Flowchart

render_flowchart
Read-onlyIdempotent

Create interactive flowcharts to visualize workflows, system architectures, or decision trees. Supports auto-layout, live status updates, and step-through playback.

Instructions

Render an interactive flowchart or diagram. USE THIS whenever the user wants to visualize a flow or structure: a workflow, data pipeline / ETL, system or software architecture, multi-agent or LLM agent design, decision tree, process map, org chart, or state machine. Nodes are rich cards (6 kinds: agent / tool / decision / data / input / output) with a type chip, name, and up to 3 property rows (e.g. model, tokens, latency); pass icon for a custom glyph. Edges support 5 typed kinds (request / response / async / stream / error) with distinct styles. Dagre auto-layout (DAG); draggable, zoomable, pannable, with a node list, minimap, and step-through playback. Status states (queued / running / done / failed / skipped) animate in place: set pollTool + statusPath for live updates, or pass a steps sequence of {nodeId: status} snapshots for manual playback. Do NOT hand-author x/y coordinates to position nodes - omit them and dagre auto-lays out the graph cleanly. Only pass x/y that were round-tripped back to you from a previous render (a user's saved drag layout), and only as a complete set covering every node; a partial set is ignored to prevent overlaps. This is a full-canvas tool, not a dashboard tile - for multi-chart layouts use render_dashboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
edgesYesEdges between nodes (form a DAG)
nodesYesNodes in the flow
stepsNoOptional playback sequence: an ordered array of {nodeId: status} snapshots. The user can step/play through them with the playback control. If omitted, a progressive reveal is derived from the graph topology.
themeNoTheme preset: boardroom, corporate, sales-floor, golden-treasury, clinical, startup, ops-control, tokyo-midnight, zen-garden, consultant, black-tron, black-elegance, black-matrix, forest-amber, forest-earth, sky-light, sky-ocean, sky-twilight, gray-hf, gray-copilot, office-red
titleYesChart title
effectsNoOverride effects: none, subtle, shimmer, neon, energetic
paletteNoOverride palette only (mix-and-match)
intervalNoPoll interval in seconds. Default: 2
pollArgsNoArguments to pass to pollTool
pollToolNoOptional: name of an MCP tool to poll for live status updates (use 'poll_http' with a preset for external APIs)
subtitleNoOptional subtitle
directionNoLayout direction. TB (top-bottom, default) or LR (left-right)
statusPathNoDot-path to a {nodeId: status} map in the poll result (e.g. 'states' or 'agents.statuses'). If omitted, the result itself is treated as the map.
typographyNoOverride typography: professional, luxury, cyberpunk, editorial, mono, bold, system, techno
interactiveNoAllow drag-to-reposition nodes. Default: true
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral details such as interactivity (draggable, zoomable, pannable), auto-layout via Dagre, status states with live polling or manual playback, and constraints on x/y usage. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but somewhat lengthy; however, every sentence serves a purpose, and key information is front-loaded. It strikes a good balance between completeness and clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly covers the tool's functionality, including interactive features, status updates, polling, and layout constraints. It equips the agent with all necessary context to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so every parameter already has a description. The description adds value by explaining usage constraints (e.g., x/y only from previous renders, statusPath dot-path, pollTool usage) and providing context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool renders interactive flowcharts/diagrams and lists specific use cases (workflow, data pipeline, system architecture, etc.). It distinguishes itself from sibling tools like render_dashboard by noting it's a full-canvas tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'USE THIS whenever the user wants to visualize a flow or structure' and provides numerous examples. It also warns when not to use it (for multi-chart layouts, use render_dashboard) and advises against hand-authoring coordinates unless round-tripped.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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