Analyze any text to obtain word count, character count, sentence count, paragraph count, reading and speaking times, plus top word frequencies. Ideal for content analysis.
Analyze text content. Returns word count, character count, sentence count, paragraph count, reading time, speaking time, and top word frequency.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text content to analyze |
Changes observed during successful MCP inspections.
v1.4.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers the safety profile, so the description adds value by listing the computed metrics. However, it does not disclose edge-case behavior such as handling of empty input, very large text, or the exact format of 'top word frequency'.
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 efficiently structured sentence that leads with the action, then lists the returned metrics. There is no redundant phrasing 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 read-only tool without an output schema, the description conveys the core output set clearly. Minor omissions like units for reading/speaking time or the definition of 'top word frequency' are small gaps, not critical missing information.
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 schema description for 'text' is 'Text content to analyze', which fully documents the single parameter. The tool description adds little beyond restating this purpose, but with 100% schema coverage the baseline 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 clearly identifies a specific verb ('analyze') and resource ('text content'), then enumerates the exact outputs. This distinguishes it from the sibling tools, none of which perform general text content analysis.
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 makes the intended use clear: analyze text to obtain quantitative metrics. It does not explicitly state when not to use it or name alternatives, but given the sibling list contains no overlapping text-analysis tool, the usage context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.