Word Counter — Count words, characters, sentences, paragraphs, and reading time in a text or uploaded document (.txt/.pdf/.docx). [category: analyze]
| Name | Required | Description | Default |
|---|---|---|---|
| file | No | Alternative: upload a .txt, .pdf, or .docx document (max 25MB). | |
| text | No | Paste the text to count. Leave blank if you are uploading a document instead. |
Changes observed during successful MCP inspections.
Input schema / properties / text / x-uiAdded value: +{
+ "multiline": true
+}Input schema / x-require-one-ofAdded value: +[
+ [
+ "file"
+ ],
+ [
+ "text"
+ ]
+]Input schema / properties / text / descriptionPrevious value: -"Text to analyse. Required unless 'file' is provided."New value: +"Paste the text to count. Leave blank if you are uploading a document instead."Input schema / properties / text / titleAdded value: +"Text to count"Input schema / requiredPrevious value: -[
- "text"
-]New value: +[]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds supported file types and the list of computed metrics, which is useful. It does not disclose output format or how reading time is estimated, but for a simple read-only analyzer this is a minor gap.
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?
A single efficient sentence that front-loads the tool's purpose and output metrics, followed by supported input types. No wasted words; the category tag is minor and does not detract.
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 low-complexity, read-only analysis tool with fully documented parameters, the description covers inputs, outputs, and file restrictions. It would benefit from a brief note on the response shape, but the tool's behavior is otherwise sufficiently clear.
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%, with both 'text' and 'file' parameters fully described. The description reinforces the input options ('text or uploaded document') but adds no meaning beyond the parameter descriptions already in 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 names a specific verb ('Count') and a clear resource: words, characters, sentences, paragraphs, and reading time. It also specifies input modes (text or uploaded .txt/.pdf/.docx), making it easy to distinguish from siblings like analyze_word_frequency or analyze_readability.
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 provides clear context: this tool is for counting text metrics from pasted text or uploaded documents. It does not explicitly exclude alternatives or state when not to use it, but the intended use case is unambiguous from the description alone.
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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