AI Flowchart

List templates

list_templates

Read-onlyIdempotent

List AI Flowchart's ready-made templates (lab programs, UML and ER for student projects, system designs, charts, app walkthroughs, code programs…). Free — no AI credits.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_templates"
  }
}

Input Schema

Name	Required	Description	Default
`type`	No	Optional board type to filter by, e.g. flowchart, erdiagram, sequence, mindmap, systemdesign, chart, codeflow, walkthrough.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 18, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety burden is met. The description adds genuinely new behavioral context: the call consumes no AI credits, which can drive agent decisions. It omits pagination and result-size behavior, so not a 5.

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

Conciseness5/5

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

One sentence naming the resource plus a short value tagline; the core purpose is front-loaded and nothing is wasted.

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

Completeness4/5

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

For a zero-argument list tool with full annotation coverage and no output schema, the description is sufficient — it names the resource, the category vocabulary, and the cost profile. Minor gaps are pagination and whether results are scoped to the user's workspace.

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

Parameters3/5

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

Schema coverage is 100% and the single optional 'type' filter is fully documented in the schema with enum-like examples, so the description need not repeat it. The category list in the description loosely maps to the filter values but adds no syntax beyond the schema.

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

Purpose4/5

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

States a specific verb (List) and resource (AI Flowchart's ready-made templates) and enumerates the template categories so an agent knows what comes back. It does not explicitly differentiate itself from the sibling open_template, but the list-vs-open distinction is inferable.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no reference to alternatives like open_template or create_diagram. The 'Free — no AI credits' note hints at when cost matters but is not framed as usage direction.

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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