Event Time Series

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

Annotations already declare safe, read-only, idempotent behavior. Description adds only high-level purpose ('get custom event counts') without detailing behavioral traits like return format, limits, or how bucketing works. No contradiction.

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?

Two short sentences, no unnecessary words. Front-loaded with the action. Could be slightly more informative but efficient for a simple purpose.

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?

Complex tool (8 params, nested filters) with no output schema. Description fails to explain return value shape, whether it aggregates over event names, or how filters interact. Insufficient for full autonomy.

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 description coverage is 100%; the description says 'configurable buckets' referring to bucket parameter but adds no significant meaning beyond what's in the schema. Baseline score applies.

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 retrieves custom event counts as time-series data with configurable buckets. Distinguishes from sibling timeseries tools like overview_timeseries and performance_timeseries by focusing on custom events.

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 a vague usage hint ('useful for analyzing event trends'), but no explicit when-to-use or when-not-to-use compared to other timeseries tools. Lacks guidance on selection criteria.

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