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

With no annotations provided, the description carries the full behavioral burden. It discloses that results are ranked by potential impact on the cohort mean, that only named checks are returned, and that facet rollups are unsupported. It does not mention output structure, pagination, or error behavior, but the core behavioral traits are clearly disclosed.

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 information-dense and front-loads the central idea, but it includes stylistic flourishes such as 'UNDERSTANDING' and 'which is the shape of a finding worth publishing' that do not add operational value. It is longer than necessary without addressing key invocation details.

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?

The tool has no output schema, no annotations, and only one documented parameter, so the description needed to explain both the return shape and how to invoke it. It explains the conceptual output well but leaves required parameters undocumented and gives no indication of what a response item looks like, making it incomplete for an agent to call correctly.

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 low at 20%, so the description needed to compensate, but it never explains the required parameters kind and slug, nor page, limit, or the meaning of the enum values. The context parameter is already described in the schema, so the description adds little to parameter understanding.

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 clearly identifies the tool's purpose: it reports the agent-readiness checks that cohort members most commonly fail, ranked by how much fixing each would move the cohort mean. It also explicitly distinguishes itself from gap_analysis, so an agent can tell the two apart without inspecting schemas.

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 explicitly positions the tool as the inverse of gap_analysis and explains the semantic difference: gap_analysis shows where a market is under-served, while cohort_failures shows where it fails the rubric. It also warns that it returns named checks only, not facet rollups, which helps an agent decide when this tool is appropriate.

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