get_report

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

No annotations provided; description compensates by detailing behavior (working and non-working metric combinations, error codes). Could explicitly state read-only nature but clearly implies retrieval.

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?

Description is front-loaded with purpose and includes dense, useful information. Slightly long but 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?

For a tool with 6 params and no output schema, description covers prerequisites, common errors, and usage boundaries. Lacks return format explanation but overall adequate.

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 coverage is 100%; description adds value with quick reference to metric keys and common traps, though parameter semantics for dimensions and limit could be enhanced.

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 retrieves aggregated statistics from AppMetrica, specifies metric key prefixes, and distinguishes from sibling tools like export_events and export_crashes.

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?

Explicitly recommends calling list_metrics first, lists common error traps (4002), and notes when not to use this tool (e.g., retention, per-user data) and what alternatives to use.

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