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

Annotations already declare readOnlyHint=true, but the description adds critical behavioral context beyond that: it details returned fields (efficiency rank, ELO, costs, FinOps flag, volatility, constraint breakdown), explains over-constrained behavior with near misses, and includes a strong warning not to re-rank. 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 moderately sized and front-loaded with the core action. It could be slightly more concise by removing the detailed field list that may be redundant with the output schema, but overall each sentence adds value. The warning is essential but feels slightly expanded.

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 has 6 parameters, full schema coverage, an output schema, and moderate complexity (constraint behavior, over-constrained handling), the description covers all key aspects: input/output, edge cases, constraints, ranking instruction, and sibling differentiation. No gaps remain.

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 adds context about constraints being 'optional' and their role in filtering, but doesn't explain parameter details beyond what the schema already provides (e.g., minElo's range is already described). The description's constraint summary is helpful but not new depth.

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 it returns a ranked top 3 for one workload under optional constraints, with a specific verb ('Pick a model') and concrete resource ('LLM Model'). It distinguishes itself from siblings like compare-llm-models by explicitly contrasting answering vs browsing.

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 when to use ('when the user wants an ANSWER') and when to use the sibling tool instead ('To browse or filter the whole catalogue instead, use compare-llm-models'). Provides clear alternatives and usage context.

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