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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds that when pair_type is omitted, the tool tries all three pair types, and explicitly lists return fields. This provides useful behavioral context beyond annotations.

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: first covers purpose and components, second lists return fields. Every word earns its place; no fluff. Front-loaded with the core function.

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 tool's complexity (3 params, output schema, annotations covering safety), the description is complete enough: it explains what pairs are checked, return fields, and behavior when pair_type is omitted. Missing details on error handling or quality metrics are acceptable given output schema presence.

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 description coverage is 100%, so baseline is 3. The description repeats that entity_a and entity_b are slugs and mentions pair types, but does not add significant new meaning beyond what the schema already provides.

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 checks compatibility and pairing quality between two components, listing specific pair types (CPU+Mobo, CPU+GPU, GPU+Monitor) and return fields. This distinguishes it from siblings (analyze_build, recommend_gpu_by_context) which focus on full builds or recommendations.

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 usage for checking specific component pairs, but does not explicitly contrast with sibling tools or mention when not to use it. The context is clear, but no exclusions or alternatives are stated.

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