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

The description goes beyond the readOnlyHint annotation by disclosing important behavioral traits: it's admin-only, uses first-party data, is crawler-filtered, and has a data start date (2026-09-15) with a note that earlier clicks exist only in platform analytics. This provides context that affects interpretation of results and is not redundant 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 a single, information-dense sentence that front-loads the core purpose and then details dimensions and constraints. While it packs a lot of information, it remains readable and efficient, though it could be broken into clearer sentences.

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 stats tool with one optional parameter and no output schema, the description covers all necessary context: what data is returned, how it's split, the data source, access restriction, and parameter default. An agent has enough to call it correctly and interpret results.

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?

The schema already fully describes the 'days' parameter with range and default. The description repeats the default and max but adds no new semantic meaning beyond what the schema provides. With 100% schema coverage, a baseline score of 3 is appropriate.

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 explicitly states the tool provides field-guide daily-series click stats, with details on data source (first-party clicks on /fg social short links), filtering (crawler-filtered), and breakdown dimensions (post, source, chapter, calendar day). It clearly distinguishes this from other account_* tools by focusing on field-guide clicks specifically.

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?

It provides a concrete use case: 'Use for "how are the daily posts doing?"' which tells an agent when to invoke it. It doesn't explicitly compare to alternative tools, but the purpose is specific enough that an agent can infer its applicability. The admin-only note also sets expectations.

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