coverage_audit

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

No annotations are supplied, so the description carries the whole burden. It discloses the ordering of results (least-populated first) and that it operates on cached datasets, but never states that it is a read-only operation, whether it scans the full dataset (cost/latency implications of 'every field'), or what a 'complete-looking' result actually means in terms of the threshold. For an unannotated tool this leaves too much unstated.

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 core capability is front-loaded in the first clause, which is good. The remaining sentences are padded with quoted colloquial framing ('the automated version of ...', 'complete-looking') that restates the same idea rather than adding new information.

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?

An output schema exists, so return-value explanation is legitimately omitted, and the read-only nature of an 'audit' is implied. But with no annotations and zero parameter documentation, the definition does not give an agent enough to invoke it correctly — particularly how 'top' and 'threshold' shape results — which is the main completeness gap for a three-parameter tool.

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% and all three parameters ('dataset_id', 'top', 'threshold') carry only titles and defaults. The description's 'least-populated first' hints at ordering and hence at 'top', but it never explains that 'top' is a result count or what 'threshold' (default 99) measures — a percentage cutoff, a minimum coverage, or something else. With three undocumented parameters, the description needed to compensate and does not.

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 gives a concrete verb and resource: scan every field of a cached dataset and return them ordered by population, least-populated first. An agent can tell this is a dataset-wide coverage audit rather than a query or a fetch. It does not differentiate itself from the sibling 'field_coverage', which sounds like an adjacent capability, 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?

It supplies a clear motivating scenario ('check field population before trusting a total') and rules out the manual alternative ('instead of hand-checking fields one at a time'). However, it never names a sibling tool as the alternative or states when this should be skipped in favor of 'field_coverage' or 'describe_dataset', so routing among siblings remains inferred.

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