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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that recommendations are drawn from 'bounded StackBench fit... only when supported,' which is a useful boundary, but it does not explain output behavior, limitations, or the meaning of the '$0.25 USDC' prefix.

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 short, but it is not well-structured for an agent. The unexplained '$0.25 USDC:' prefix consumes space without adding clarity, and 'only when supported' is ambiguous. The core verb is front-loaded, but the remaining content is vague and under-specified.

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 42 parameters, 10 enums, and four siblings, this single-line description is severely incomplete. It omits what 'StackBench' and 'bounded' mean, how recommendations are produced, what inputs are expected, and what constraints apply. The output schema helps, but it cannot compensate for the lack of domain and workflow context.

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?

With 42 parameters and 0% schema description coverage, the description needed to explain how parameters relate to the recommendation process, but it mentions none of them. The phrase 'fit, performance, confidence, evidence, caveats, and economics' hints at concepts, but provides no concrete parameter-level meaning or guidance.

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 identifies the core action: 'recommend what to buy or run', and it names the input dimensions considered (fit, performance, confidence, evidence, caveats, economics). This distinguishes it from sibling tools like search_evidence or predict_performance, though it does not explicitly call out the differences.

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?

There is no explicit guidance about when to use this tool versus alternatives such as check_deployment_fit, generate_launch_config, or predict_performance. The phrase 'only when supported' hints at a condition, but it is vague and does not say when the recommendation should be sought or when a sibling is more appropriate.

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