generate_diagram_from_text

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it generates diagrams from text, supports specific diagram types, and returns a link to view/edit the diagram. It could improve by mentioning potential limitations like generation time or accuracy, but it covers core functionality well.

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

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

The description is well-structured and front-loaded with the core purpose, followed by usage guidelines and return information. It avoids unnecessary repetition, though it could be slightly more concise by integrating the diagram type list more smoothly.

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

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

For a tool with no annotations and no output schema, the description provides good context: it explains what the tool does, when to use it, supported diagram types, and the return format (a link). It could be more complete by detailing error cases or output specifics, but it covers essential aspects adequately.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond the schema, only implying that 'content' should be descriptive natural language. This meets the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose with a specific verb ('generate') and resource ('software engineering diagram from a natural language description'). It distinguishes itself from siblings by specifying the input source (natural language) rather than ASCII, image, JSON, or Mermaid formats.

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

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

The description provides explicit guidance on when to use this tool, listing specific user requests ('create a diagram', 'show me a flowchart'), keywords ('adm' or 'ai diagram maker'), and contexts (visual representation of code, systems, processes, or data flows). It implicitly distinguishes from siblings by focusing on natural language input.

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