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

The phrase 'input discarded' and the schema notes ('no disk access', 'discarded after the call') provide some privacy-related behavioral disclosure. However, with no annotations and no output schema, the description still fails to state what the tool returns, whether it performs network access, or how errors surface.

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 extremely short, but this is under-specification rather than effective conciseness. It omits the core operation and leaves the agent to infer the tool's behavior from the name alone.

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 9 optional parameters, no annotations, and no output schema, a one-line fragment is completely inadequate. An agent cannot determine which parameter is the subject of the check, what 'ok' means, or what a successful or failed result looks like.

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?

The input schema has 100% description coverage, documenting each of the 9 parameters. The tool description itself adds no parameter-level meaning, but the schema already carries that burden, so a baseline score of 3 is appropriate.

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 'z-base-32 charset, input discarded' restates the tool name without a verb; it never states whether the tool validates, encodes, decodes, or checks shape. It also offers no differentiation from the many sibling shape-check tools.

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?

No guidance is given on when to use this tool versus alternatives such as validate-json, domain-shape, or search-query-len. There is no context, no prerequisite, and no exclusion criteria.

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