datasets_steam_charts_search

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

With no annotations, the description carries the full transparency burden and does well: it explains the search index structure (one document per chart × country × snapshot × rank), history accumulation, and default snapshot behavior. It does not describe pagination quirks or return format, but those are partially visible in the schema and less critical for safe invocation.

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 four dense but well-structured sentences. It front-loads the core purpose and packs the data model, chart types, defaults, and key parameter interactions without fluff or redundancy. Every sentence adds value.

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?

Despite having 8 parameters and no output schema, the description covers the essential context: dataset contents, document structure, chart types, default date, and country conventions. It could say a bit more about full-text `q` search behavior and pagination constraints, but the schema descriptions already cover those parameter details.

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?

The schema already documents all 8 parameters, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining chart enum values, the default date behavior, country mapping, and the app_id + sort=date_desc combination for time-series lookups, exceeding the baseline.

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 searches the steam-charts dataset, which contains daily snapshots of Steam's player-count and sales charts. It names the specific chart types (`most_played`, `concurrent`, `top_sellers`) and their meanings, distinguishing this tool from sibling Steam tools like `datasets_steam_playercounts_search` and `datasets_steam_news_search`.

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 strong operational guidance: no `date` returns the latest snapshot, pairing `app_id` with `sort=date_desc` fetches an app's history, and country is `global` for player-count charts but an ISO code for `top_sellers`. It doesn't explicitly name sibling alternatives or exclusionary conditions, but the context is clear enough for an agent to decide when to use this search tool.

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