Text statistics

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

With no annotations provided, the description carries the transparency burden. It discloses the key behavioral boundary ('No filesystem, network, or subprocess access') but does not explain counting conventions, edge cases, or the exact return format.

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, front-loading the core purpose and then stating constraints. Every word earns its place with no redundancy or filler.

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 single-parameter tool with no output schema, the description adequately communicates purpose, scope, and safety boundaries. The only minor gap is the lack of explicit mention of the return shape, but it is reasonably inferred from the stated behavior.

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% because the only parameter 'text' already has a clear description ('Text to measure'). The tool description adds useful context that the text is counted, but it does not provide additional parameter-level syntax or usage details beyond the schema.

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 uses a specific verb ('Count') and names the exact resources ('words and characters'), while clarifying the in-memory scope. This clearly distinguishes it from the sibling tool 'echo', which is about outputting text, not computing statistics.

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?

The description implies usage context: this is a safe, memory-only text measurement tool, and it explicitly rules out filesystem, network, or subprocess access. However, it does not explicitly state when to prefer this over alternatives like 'echo' or provide concrete use-case guidance.

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