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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable context beyond annotations: data originates from server logs, logging began 2026-07-23 with no earlier history, and 180-day retention. It also explains why the data is absent from page analytics. No contradiction exists; the 'Read-only' note is consistent with annotations.

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 five sentences with zero filler. It opens with the core purpose, immediately states the key caveat (invisible to page analytics), then covers grouping/filtering, data history, retention, and read-only status. Information is front-loaded and 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 read-only query tool with no output schema, the description covers all essential calling context: data source, scope (heista.co pages), available groupings/filters, data start date and retention, and read-only nature. It does not describe the exact response shape, but that is not required without an output schema. Minor gaps like a full bot list are handled by the schema.

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%, so each parameter is already documented with detailed semantics (e.g., path_prefix is 'Anchored – this is the one you want'). The tool description only gives a high-level overview ('Group by bot, page, or date; filter by bot or path'), which adds no new information beyond the schema. Baseline 3 is appropriate given the high schema coverage.

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 specifically states the tool's verb+resource: server-logged crawler fetches of AI engines (GPTBot, ClaudeBot, etc.) and search crawlers (Googlebot, Bingbot) on heista.co pages. It explicitly contrasts with page analytics, and the ability to group and filter is clear. This distinguishes it from sibling tools like fleet_analytics_overview and fleet_gsc_*.

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 clearly implies when to use this tool: when you need crawler fetch data that is invisible to page analytics. It states the data source is server logs, and that crawlers never run the tracking script. However, it does not explicitly name alternatives or provide exclusion criteria (e.g., 'use fleet_gsc_query for Googlebot-only data'), so guidance is contextual but not fully explicit.

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