text_stats
Count characters, words, sentences, paragraphs and lines, and estimate reading time.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Count characters, words, sentences, paragraphs and lines, and estimate reading time.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, non-destructive, and closed-world, so the safety profile is fully covered. The description adds what metrics are computed but does not describe the return format, how reading time is estimated, or how lines/paragraphs are counted — details an agent might need.
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 a single efficient sentence that front-loads the action and lists all metrics without any extraneous text. 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 is simple and annotations cover behavior, but there is no output schema and the description does not explain the return shape (e.g., whether counts are returned as an object, in what order) or the basis of reading-time estimation. It is adequate but leaves clear gaps for an agent to infer.
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 one parameter ('text') with 0% schema description coverage. The description implies that the input text is what gets analyzed, but it adds no explicit meaning beyond the parameter name, such as required format, size limits, or handling of empty strings. Baseline is adjusted for one param with no schema documentation.
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 states a specific action (count) and enumerates the exact resources/metrics: characters, words, sentences, paragraphs, lines, plus reading time. It is clear what the tool does, though it does not explicitly differentiate itself from sibling tools, which is less necessary here since none overlap.
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?
Usage is implied by the listed metrics, but there is no explicit guidance on when to use this tool versus alternatives, nor any mention of prerequisites or exclusions. For a simple utility tool this is minimally adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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