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

With no annotations, the description must carry the behavior burden. It does reveal a non-obvious behavior—values are discarded—and counting implies a read-only operation. However, it does not state the return type or clarify whether the input object itself is consumed, so the behavioral picture is only partially complete.

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 two short sentences with no filler; the action is stated first and the value-discarding caveat is placed immediately after. Every word earns its place.

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 simple counting tool, the description plus a fully described schema is minimally viable: an agent can infer that keys are counted and values are placeholders. But with no output schema, no annotation, and a 9-parameter schema whose relationship to the JSON object is ambiguous, the definition is not fully actionable without extra inference.

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 100%, so the 9 parameters are individually documented and the baseline is 3. The description adds the global insight that only the presence of keys matters, but it does not resolve which parameter represents the JSON object to count or how the 9 unrelated strings should be populated.

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 identifies a specific operation—counting keys in a JSON object—and adds the useful behavioral note that values are discarded. This separates it from validate-json and the shape-check siblings, which validate or return ok/not-ok rather than count. It loses a point because it does not state whether the JSON object is the tool-call arguments object or a JSON value passed through one of the parameters.

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 when-to-use guidance, no mention of alternatives, and no exclusions. The active phrasing 'Count keys...' implies the obvious use case, but an agent is not told how to choose this over validate-json or the other count/check tools.

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