project_statistics

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

No annotations are provided, so the description carries the full burden. It adds useful behavioral context: performance expectations (1-3s), data source ('pre-calculated metrics from the code graph'), and interpretation of health score (below 7/10 indicates issues). This goes beyond basic read-only implication, though it doesn't explicitly state 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 structured with clear sections (purpose, usage, performance, workflow, tip), making it scannable. It's slightly verbose for a zero-parameter tool, but every section adds value—especially the workflow and tip. It earns a 4 rather than 5 due to length, but it's well-organized.

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 no parameters and no output schema, the description is remarkably complete: it explains the tool's purpose, high-level metrics, performance characteristics, integration into a workflow, and how to interpret the health score. It covers all necessary context for an agent to decide when to use this tool and what to expect.

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?

Input schema has zero parameters, so the baseline is 4. The description adds meaning by listing the metrics the tool calculates (file counts, language distribution, complexity trends, health score), which helps the agent understand what the tool outputs even without an output schema.

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 a specific verb+resource: 'Get comprehensive project statistics and health metrics,' then details what it provides (file counts, language distribution, complexity trends, health score). This distinguishes it from sibling tools like find_definition or complexity_analysis, which are more focused.

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?

Provides explicit use cases: 'project assessment, progress tracking, generating project reports.' Includes a workflow suggestion (analyze_codebase → project_statistics → drill down) indicating when to use it relative to other tools. Does not name alternatives explicitly but gives clear contextual guidance.

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