Count words, characters, and lines in provided text to measure content length and structure for writing, editing, or validation tasks.
Count words, characters, and lines in text. Free and unlimited in this sample.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to analyze |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses the cost/quota posture ('free and unlimited in this sample'), which is useful, but says nothing about whether the operation is pure/read-only, output ordering, or how edge cases (empty text, Unicode) are handled.
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 the core capability front-loaded and no filler. Every clause carries 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?
With no output schema, the description lists the three returned metrics, which adequately covers the return values for this simple tool. Minor gaps remain around counting conventions and output shape, but nothing essential is missing for a one-parameter utility.
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?
There is a single parameter with 100% schema coverage ('Text to analyze'), so the schema already does the work. The description adds that the input yields word, character, and line counts, which clarifies what the text is measured against, but adds no format or constraint detail.
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?
States a specific verb ('Count') and the exact metrics produced (words, characters, lines), so the operation is unambiguous. It does not explicitly differentiate itself from the siblings summarize or extract_keywords, but the metric-counting purpose is distinct enough to infer.
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 statement of when to use this tool versus summarize or extract_keywords, which also take text. 'Free and unlimited in this sample' hints at cost considerations but says nothing about selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.