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

Goes well beyond the read-only/idempotent annotations: it discloses that shares are null below ten named-product assignments, that 'several' and 'nobody' are excluded from the denominator, that a zero/null competitor_set_id means no set was recorded, and how prior_status/prior_window gate whether a change may be stated. These are non-obvious data-quality rules an agent could not recover from the schema or 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 purpose statement is front-loaded and the remaining sentences each carry a distinct rule about sets, shares, or prior windows. It is dense but justified by the amount of reporting semantics; the one redundancy is that 'no set recorded' is stated twice via current_set_id and zero competitor_set_id.

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?

With no output schema, the description does the necessary work of sketching the return shape: totals, daily trend points with fields, and prior blocks with share_of_statement. The remaining gap is input-side — intent and platform are undocumented — but the output and comparability semantics are thorough.

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 0%, so the description carries the full burden, and it only covers 'window' indirectly ('over 30 or 90 days'). The 'intent' and 'platform' parameters are never mentioned, leaving two of three inputs entirely unexplained in both schema and description.

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?

Opens with a specific verb and resource: 'Read positioning match counts and share over 30 or 90 days.' That is clearly distinguishable from generic mutation or listing tools. However, it never differentiates itself from close siblings such as devtune_get_competitive_position or devtune_list_positioning_statements, leaving the agent to infer which positioning view to pick.

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?

Usage is implied rather than stated: the description explains how to segment trend points and when not to report a change, which is reporting guidance in practice. There is no explicit 'use this when…' clause and no named alternative for related questions, so the agent must infer the selection conditions.

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