parse_xmind

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

Since no annotations are provided, the description must address behavior. It discloses support for both Zen and Legacy formats and explains differences between Markdown and JSON outputs (token efficiency, structure summary, metadata). This adds useful context beyond a minimal 'parse' statement, though it stops short of detailing error cases or side effects.

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 three sentences, front-loaded with the primary action. Each sentence adds value: purpose, format guidance, and compatibility. No redundant or filler content.

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 simple tool with two parameters and no output schema, the description sufficiently covers the primary action, output options with recommendations, and file format compatibility. It does not detail error handling or file size limits, but that depth is not necessary at this level of complexity.

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 coverage is 100% and both parameters are already well-described in the schema. The description repeats the format recommendation and mentions JSON contents, but it does not add new parameter-level semantics beyond the schema. Therefore the baseline score of 3 is appropriate.

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 identifies the tool's purpose: 'Parse an entire XMind document (.xmind file) and return formatted output (Markdown or JSON).' The verb 'parse' and resource 'XMind document' are specific, and the word 'entire' distinguishes it from sibling tools like search_xmind_nodes or get_xmind_node_branch.

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 offers guidance on choosing output format ('Markdown format is more token-efficient and recommended for large documents'), but it does not explicitly state when to use this tool versus the sibling tools. The 'entire' qualifier implies for full-document processing, but there is no direct comparison or exclusion.

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