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

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds significant behavioral details beyond that: default 'slim' vs 'full' response, truncation of mitigations/examples, the 'cve_count' lower-bound nuance, rate limits (30/hr, 500/hr), and 404 behavior. This gives the agent confidence in side effects and data semantics.

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 long but densely packed. It front-loads the purpose, then logically flows into default behavior, parameter effect, return fields, usage guidance, error handling, and rate limits. Every clause earns its place, though the final 'Returns { ... }' list partially duplicates output schema information. It is efficient for the complexity, but slightly verbose.

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?

For a tool with two parameters, one optional, and a rich output schema, the description is exceptionally complete. It covers default return shape, full detail mode, data semantics (lower-bound cve_count), error conditions, rate limits, and workflow integration with cve_lookup and cve_search. There are no significant gaps in what an agent needs to know to invoke and interpret results correctly.

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 the baseline is 3. The description adds useful semantics: it clarifies the effect of the 'include' parameter (slim vs full) and notes that 'total_mitigations / total_examples are always honest pre-truncation counts.' For 'cwe_id', the schema already provides format and common values, and the description does not repeat that unnecessarily. The added nuance about total counts and extended_description null behavior goes beyond schema descriptions.

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's function: 'Look up MITRE CWE catalog record from research view 1000.' It uses a specific verb ('look up') and resource ('CWE catalog record'), and adds scope ('research view 1000'). This distinguishes it from sibling tools like cve_lookup and atlas_technique_lookup, which focus on different databases. The purpose is unambiguous and not a tautology.

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 provides explicit guidance: 'Use after cve_lookup or kev_detail to understand the underlying weakness category; chain with cve_search(cve_id=...) to enumerate all matching CVEs.' This tells the agent exactly when and how to use the tool relative to others. It also notes the 404 error condition, adding practical usage context.

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