playstation_suggest

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so well. It discloses that matching is loose and upstream-ordered, that the upstream API ignores limit values above 20, that cc affects currency, and that l uses the locale's primary language for text. It also states the data is credential-free public PlayStation Store data, which signals no auth setup is needed. The only minor gap is not describing pagination or error behavior, but for a suggestion endpoint this is adequate.

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 a single dense paragraph but every sentence earns its place. It front-loads the core purpose, then covers return fields, matching behavior, parameter semantics, and credential requirements in a logical order. There is no filler, no repetition of the schema, and no extraneous detail. The length is appropriate for the amount of behavioral nuance it conveys.

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 4-parameter tool with no output schema and no annotations, the description is nearly complete. It covers what the tool returns, how matching behaves, what each parameter does, and the credential-free nature of the data. The only missing piece is an explicit statement about the response shape or error cases, but the description already enumerates the per-match fields, which largely compensates for the absent output schema.

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 the baseline is 3. The description adds meaningful semantics beyond the schema: it explains that limit is capped at 20 because the upstream API does not honor higher values, that cc selects the store region and price currency, and that l accepts a locale like en-US with the primary language used for text. This goes beyond the schema's terse 'Language code' and 'Store country code' descriptions, so a 4 is warranted.

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 opens with a specific verb and resource: 'Get PlayStation Store search suggestions for a term.' It then enumerates the exact fields returned per match (id, name, classification, platforms, publisher, release date, price, image, store URL), which makes the tool's purpose unmistakable. It also distinguishes itself from sibling tools like playstation_search and playstation_browse by framing this as typeahead-style suggestions rather than a full search or browse operation.

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 explicitly states when to use this tool: for partial or full terms needing typeahead-style suggestions. It also gives clear exclusions: matching is 'upstream-ordered and loose... not a ranked exact-substring search,' which tells an agent not to use this when ranked exact results are needed. It further explains the role of each parameter (limit caps suggestions, cc selects region/currency, l selects language), which is effectively usage guidance beyond the schema.

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