export_claude_md

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

No annotations are provided, so the description must disclose behavior. It states it generates a document but does not clarify whether it writes to a file, returns content, or has side effects. It also fails to mention any permissions, limits, or output format, leaving key behavioral aspects ambiguous.

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 a single, front-loaded sentence with a clear verb and object, followed by a parenthetical list of content categories. It is concise and contains no unnecessary words.

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 lack of annotations and output schema, the description should explain return values, side effects, and parameter behavior. It only covers purpose and content categories, leaving critical operational details absent for an 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 schema has 0% description coverage for the only parameter, max_constraints. The description broadly references 'top constraints' but does not explain that max_constraints limits that section, nor its units or effect on other sections. The parameter semantics are only indirectly inferable.

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 uses a specific verb ('Generate') and identifies the resource ('CLAUDE.md document from the knowledge graph'), and it lists the included content categories (top constraints, recent decisions, known bug regions, co-edit patterns), distinguishing it from sibling tools that query individual aspects.

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 implies the tool is for producing an aggregated CLAUDE.md from knowledge graph data, but it does not explicitly state when to use this tool versus querying individual components via siblings like get_constraints or get_decision_log. It lacks explicit exclusions or alternatives.

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