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get_anr_rate

Retrieves daily ANR rate and user-perceived ANR rate from Android Vitals to detect when user-perceived ANR exceeds 0.47% and avoid Play Store ranking penalties.

Instructions

Fetch ANR (Application Not Responding) rate from Android Vitals.

Returns daily anrRate, userPerceivedAnrRate, and distinctUsers by version code. Bad behavior threshold: userPerceivedAnrRate > 0.47% may cause Play Store ranking penalties.

Args: package_name: Package name, e.g. com.example.myapp days: Past days to include (default 7, max 30). version_code: Optional version code filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
package_nameYes
daysNo
version_codeNo
Behavior4/5

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

With no annotations, the description must disclose behavior. It explains the tool fetches data from Android Vitals, returns daily metrics, and includes a performance penalty threshold. It does not mention side effects, authentication, or error handling, but sufficiently describes the read operation output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (3 sentences for main info, plus parameter list) and front-loaded with the core purpose. Every sentence adds value, no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple fetch tool with 3 parameters and no output schema, the description covers return fields and a key threshold. It could be more complete by mentioning error cases or data availability, but overall it adequately informs an AI agent about the tool's capabilities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description fully compensates by explaining each parameter: package_name with an example, days with default and max, version_code as optional filter. This adds critical meaning beyond the schema's type and default values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with 'Fetch ANR rate from Android Vitals', which clearly states the action and resource. It also specifies the returned data (anrRate, userPerceivedAnrRate, distinctUsers) and a key threshold, distinguishing it from sibling tools like get_crash_rate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a threshold for interpreting results but does not explicitly state when to use this tool versus alternatives like get_crash_rate or get_vitals_summary. It lacks explicit guidance on prerequisites or exclusions.

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

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