visualize_graph

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

With no annotations, the description carries the full burden. It discloses the output format (Mermaid) and notes that raw Mermaid text is useful even if clients don't render it. However, it does not mention whether the operation is read-only, has any side effects, or requires specific session state, leaving some uncertainty.

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 two sentences, front-loaded with the core purpose and followed by a brief usage note. Every sentence earns its place, with no filler or repetition.

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?

Given the tool's simplicity, the description covers the essential purpose, output format, and usage context. The schema handles parameters, and the description adds the key context about when to use it. It lacks explicit safety or side-effect details, but that is a minor gap for a likely read-only export tool.

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?

The input schema covers 100% of the parameters with descriptions, so the baseline is 3. The description does not add any additional parameter semantics beyond the schema, making it adequate but not enhanced.

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 states a specific verb ('Export'), a clear resource ('a subgraph'), and a concrete output format ('Mermaid diagram'). This distinguishes it from sibling tools like export_knowledge or serialize_knowledge, which might have different output formats or purposes.

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 explicitly states when to use the tool: 'Use this after query_subgraph to show the structure.' It provides clear context but does not mention alternatives or when not to use it, so it falls short of a fully explicit when/when-not guideline.

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