get_histogram

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

With no annotations, the description carries the transparency burden. It discloses output (per-bucket counts, median/p95/p98) and the raw flag's effect, plus lossless bucket preservation. It doesn't mention permissions, rate limits, or failure behavior, but for a read-only get operation this is adequate.

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 compact (three sentences) and front-loaded with the core purpose. It avoids redundancy and flows logically from purpose to behavior to raw mode, with no wasted words.

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?

Given the tool has 14 parameters and no annotations, the description is not fully complete. It relies on the output schema for return values and on get_summary for behavioral context, but it doesn't describe which parameters are needed or how they interact. Still, it covers the main query type and output structure.

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 0%, so the description must compensate. It only explains raw=True and vaguely references date_comparator. The other 12 parameters (app, timer, date, browser, etc.) are completely unexplained, leaving the agent to guess their meaning.

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 the tool's purpose: providing a histogram distribution with per-bucket counts and percentiles. It names the mPulse query type and distinguishes itself from get_summary by referencing its behavior.

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?

The description references get_summary for time selection and drilldowns, giving a clear comparison point for when to use this tool. It also explicitly notes raw=True for untouched JSON. However, it doesn't explicitly state exclusion cases or when to prefer other sibling tools.

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