Query Similarity

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds two genuinely non-obvious traits: that only skill-input models accept a list (a constraint the schema does not enforce, since input allows arrays unconditionally) and that upstream warnings are preserved. It says nothing about scoring behavior or how min_score affects results.

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?

Three short sentences with the capability statement front-loaded and no filler. It is efficient, though the example list consumes most of the text relative to the substantive constraints.

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?

An output schema exists, so return values need not be explained. However, for a six-parameter query tool with zero schema documentation, leaving four parameters and the model-selection decision unexplained is a material gap an agent cannot resolve from structured data alone.

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 0% across six parameters, so the description carries the full burden. It partially compensates for `model` (via examples) and `input` (via the list constraint), but limit, min_score, filter_ids and lot_version are left entirely undocumented, including the meaning of the 0.5 min_score default and the 6/7 lot_version switch.

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?

States a specific verb and resource ("Query a Similarity model") and enumerates concrete model values (soc, skill, lotspecocc-skill, skill-lotocc), which tells an agent what domain it operates in. It does not distinguish itself from siblings such as find_similar_skills or get_similarity_metadata, so an agent must still infer which entry point to use.

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 lists example model names but gives no guidance on when to choose this tool over the similarity-adjacent siblings, nor which model suits which question. There are no stated preconditions or exclusions beyond the single list-input constraint.

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