feature_separate_batch_eval_check

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

With no annotations, the description carries the full burden, and it does disclose one behavioral trait: 'never uses network,' which tells the agent this is a local/safe read-style operation. That is genuinely useful. However, it says nothing about read-only status, error behavior, what 'comparison readiness' means if the cohort fails validation, or any side effects, leaving significant behavioral gaps for a tool with zero annotation coverage.

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 compact sentence with no filler and front-loads the action. It is efficient, though the brevity comes at the cost of completeness rather than being a model of useful concision.

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 tool with two parameters (one required, zero schema descriptions), no annotations, and four similar siblings, the description is too thin. It omits all parameter meaning, provides no routing guidance versus siblings, and only hints at the validation outcome despite an output schema existing. The one behavioral disclosure ('never uses network') is the sole substantive addition.

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%: neither 'cohort_id' nor 'minimum_support' has a description in the schema. The tool description mentions neither parameter, so it does not compensate at all. The agent has no idea what format cohort_id takes, what minimum_support controls, or how the default of 10 applies.

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 states a verb ('Validate') and resource ('one cohort') and adds the deliverable ('show comparison readiness'), which is clearer than a bare name. However, it does not distinguish this tool from its four siblings (status, tag, run, insights), all of which share the eval-batch prefix. An agent gets partial understanding of the purpose but cannot confidently route between the siblings based on the description.

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?

There is no explicit guidance on when to use this versus the sibling tools. The phrase 'show comparison readiness' implies a preparatory check step, but neither alternatives nor exclusions are named. The agent must infer usage from context alone.

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