explain

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

Describes what the tool combines (call-graph, semantic search, quality metrics) and implies it is a read operation. With no annotations provided, the description carries the full burden and does an adequate job, though it does not discuss performance or error handling.

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?

Two sentences, highly efficient, front-loading the purpose and usage. Every word earns its place with no redundancy.

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 existence of an output schema, the description adequately covers behavior, usage, and parameter guidance. It does not explicitly differentiate from siblings like 'analyze' or 'map', but the purpose is clear enough that an agent can decide appropriately.

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%, so baseline is 3. The description adds value by explaining verbosity usage ('summary' and 'full'), but slightly mismatches the schema's default 'detailed' and misses 'detailed' in the example, causing minor confusion.

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?

Clearly states it explains an unfamiliar symbol by combining call-graph, semantic search, and quality metrics. However, it does not explicitly differentiate from listed sibling tools like 'analyze' or 'map'.

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?

Explicitly states when to use ('onboarding to an unfamiliar symbol') and mentions an alternative action ('so Read is often unnecessary'). Also provides guidance on verbosity levels with concrete examples.

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