datasets_apps_charts_search

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

No annotations provided, so description must carry full burden. It describes a read search operation without side effects, but does not explicitly state read-only or mention any behavioral traits like rate limits or auth requirements. Adequate but not exceptional.

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?

Four well-structured sentences front-loading the main purpose, then providing key usage details and parameter explanations. 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?

No output schema, so description should explain return fields. It mentions document structure but not specific fields. For a search tool with 11 parameters, it covers usage well but omits output details, leaving some uncertainty for agents.

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?

Input schema covers all 11 parameters with descriptions (100% coverage). Description adds semantic value by explaining document structure, default behavior, and usage tips (e.g., pairing app_id with sort=date_desc), going beyond schema descriptions.

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?

Description clearly states it searches the app-charts dataset, specifying data source (iOS App Store and Google Play), storage structure (one document per chart × snapshot × rank). Distinguishes from sibling tools like datasets_apps_search by focusing on charts data.

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 usage patterns: default date returns latest snapshot, pairing app_id with sort=date_desc for rank history. Explains enums for store, chart type, and sort. Does not explicitly mention when not to use, but context is clear.

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