datasets_steam_news_search

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

With no annotations, the description carries full burden. It discloses the search scope (tracked apps), deduplication, and sort defaults. Does not mention rate limits or update frequency, but for a search tool 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?

Three sentences with clear front-loading: first sentence defines purpose, second adds data model, third details filtering and sort. No fluff, every sentence earns its place.

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 no output schema, the description explains the document structure (appid × gid) but not the fields returned (e.g., title, content, date). Pagination limits are noted. Slightly incomplete for a fully self-contained definition.

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?

Adds significant meaning beyond schema: explains q covers title+contents, app_id is exact, sort enum values, and page_size constraint (max 100, product with page <= 10000). Schema coverage is 100%, yet description enriches understanding.

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 searches the 'steam-news dataset' with specific verbs ('search', 'filter', 'sort'). It distinguishes from sibling tools by specifying the dataset and the data model (one document per appid × gid, latest kept), making its scope unique.

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?

Provides explicit guidance on when to use app_id vs q filter and sort options. Mentions the deduplication behavior ('latest items per app kept'), aiding appropriate usage. Lacks explicit comparison to alternative tools like steam_news, but the context is clear enough.

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