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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds meaningful behavior beyond that: results are newest-first, and 'ready_only' defaults to true so only successfully completed runs are returned by default, which is a real filtering trap for an agent. It does not cover auth requirements or rate limits, keeping it out of the 5 range.

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?

Front-loads the purpose in one line, then the returned-field summary, then the Args block. Every sentence is functional. The metrics enumeration is a long list, but with no output schema it is load-bearing rather than filler.

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 usefully enumerates what each run summary contains (visibility score, mention rate, brand rank, competitors, topic context) plus all filtering and pagination controls. Nothing critical to invoking it correctly is missing, though the relationship to get_research_run remains unaddressed.

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 only 17%, so the description carries most of the parameter burden and largely delivers: brand_id (required), report_type enum values, ready_only semantics, and limit/offset ranges and defaults are all spelled out. Only user_intent is undocumented here, though the schema itself covers that one, so semantic compensation is strong but not exhaustive.

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?

States a specific verb and resource with ordering: 'List prompt research runs for a brand (newest first).' An agent immediately knows this is a collection-retrieval tool. However, it never differentiates itself from the very similar siblings get_research_run (singular) or get_latest_research, so it falls short of a 5.

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 explains how each filter narrows the result set (report_type, ready_only default of true, pagination), which implies usage. It does not, however, state when to pick this tool over get_research_run, get_latest_research, or get_reports, leaving the agent to infer the boundary.

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