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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real behavior beyond that: the productFit >= 60 selection rule for autopilot/topic adds, the lowFit and catchAll pool semantics, covered/excluded flag meaning, and that the call is free. This is substantive context not derivable from structured fields.

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?

It is front-loaded with the core purpose, but the body is a single dense paragraph of nested parentheticals spanning ~180 words, which is hard to scan. Most clauses carry information, but the lack of any structure or line breaks hurts readability.

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 takes on the full burden of describing return values and does so thoroughly: topic structure, pillar/member keywords, volume/difficulty/intent, addableCount, coveredBy, productFit, and the catchAll pool. Nothing an agent needs to interpret the response is missing.

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 100%, so the baseline is 3, but the description adds meaning the schema omits: limit/offset are said to page 'over topics' (the schema only says 'for paging'), and it summarizes the filter/sort surface (intent, maxKd, search; score/volume/kd). keywordLimit is left to the schema, keeping it from a 5.

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 opens with a specific verb+resource+scope: 'The keyword clusters (topics) Blawgy researched for this site.' It immediately distinguishes itself from siblings like get_keyword_recommendations and list_my_keywords by describing the returned structure (pillar keyword, member keywords, addableCount, covered/excluded flags).

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 gives explicit conditional routing: 'If hasResults is false and processing is true, research is running (get_research_status); if neither, call run_keyword_research,' and names add_to_plan for the scheduling use case. This is exactly the when/when-not/alternatives guidance the dimension asks for.

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