stats

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

With no annotations, the description fully covers behavior: states read-only, no side effects/auth/rate limits, explains performance impact of include_token_total, and clarifies project_id semantics (null vs omit). No contradictions.

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 with no redundant words. Key information is front-loaded (purpose, counts), and every sentence adds distinct value. Highly efficient.

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 three parameters, no output schema, and no annotations, the description adequately covers functionality, parameter behavior, and use cases. It explains return values conceptually (counts, by_project breakdown). Could be more explicit about the exact return shape, but sufficient for selection and invocation.

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 descriptions exist in schema. However, the tool description adds value: it clarifies the default for top_tags (10) and explains the performance trade-off for include_token_total, which the schema does not. Slight extra information earns a 4.

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?

Description clearly states the tool aggregates counts (file_count, untagged_count, etc.) for a scope, and distinguishes from the sibling tool diff_against_disk which is for drift. The verb 'Aggregate' and resource 'counts' are specific.

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 says 'Use as a cheap dashboard or to spot untagged content for cleanup; for live disk-vs-index drift use diff_against_disk.' This provides a clear when-to-use and an alternative, which is excellent guidance.

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