ua_graph_summary

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by disclosing the specific return content (node and edge counts), which goes beyond what annotations provide. However, it does not mention any side effects or further behavioral traits.

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 long with no extraneous information. The first sentence front-loads the purpose, and the second adds output detail. Every word earns its place.

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 zero parameters, no output schema, and rich annotations, the description fully explains what the tool does and what it returns. It is complete for its simplicity and purpose.

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 is empty with 100% coverage, so the description does not repeat parameters. It adds meaning by explaining the purpose and output of the tool, which the schema alone cannot convey. This goes beyond the baseline of 3.

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 gets a 'high-level statistical summary' of the codebase knowledge graph, specifying it returns node and edge counts. This verb+resource combination uniquely identifies it from the sibling tool 'ua_architecture_report' which likely provides a different kind of report.

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 use for 'gauging project size' but does not explicitly state when to use this tool vs. the sibling tool 'ua_architecture_report'. No exclusions or alternatives are mentioned, so guidance is solely implied.

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