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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that values are discarded, which is useful, and implicitly frames the tool as non-mutating. It does not mention return shape, error cases, or whether external access occurs, but for a counting operation this is a moderate rather than severe gap.

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?

Two short sentences with no filler. The main action ('Count keys in a JSON object') is front-loaded, and the only extra clause ('Values discarded') states an important behavioral constraint. 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?

The tool has nine optional parameters and no output schema or annotations, so the description needs to explain how the count is obtained and what the result looks like. It does neither: it never says that the counted object is the argument object itself, which parameter to inspect, or what the response contains. This leaves too much to inference for an AI agent to call it reliably.

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 parameters are individually documented and the baseline is 3. The description adds no parameter-level meaning, but it also does not need to, because each schema property already explains its own discarded/validated purpose. Ambiguity remains about which property represents the JSON object to count.

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 specific verb and resource: count keys in a JSON object. It also adds a behavioral qualifier ('Values discarded') that distinguishes it from a JSON validation or inspection tool. However, it does not explicitly tie the action to any of the nine schema properties, so a reader must infer that the JSON object is the set of provided arguments.

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 guidance about when to choose this tool over siblings such as validate-json or hn-front-count, and no mention of when not to use it. The only implied use is the literal counting of keys; no context, prerequisites, or alternative routing is provided.

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