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x402node_text_stats

Calculate word count, character count, line count, paragraph count, sentence count, and reading time for any text input. Micropayments via USDC on Base.

Instructions

Text statistics / word count / character count / line counter / text analyzer / reading time estimate / paragraph counter / sentence counter / text length / wordcount API / count words in text. Get word/char/line/paragraph/sentence count and reading time estimate.

Price: unknown on Base (auto-paid in USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to analyze (required, max 64k)
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions only the 'max 64k' input limit (in schema description) and a note about pricing, but fails to describe output format, potential privacy concerns, or that the tool is read-only and safe. The payment note is tangential.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is adequately sized but contains redundant synonyms ('text statistics / word count / ...' and 'count words in text') that could be condensed. The core information is front-loaded in the second sentence, but the opening is noisy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter tool, the description conveys the core functionality well. It lacks details about the return format (e.g., whether results are an object or array), but the tool's straightforward nature and absence of an output schema make that omission less critical. The payment note is an odd inclusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description only repeats the parameter's existence ('Text to analyze (required, max 64k)') without adding semantic context like encoding, language support, or special characters handling. It adds minimal value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly lists all statistics provided (word count, character count, etc.) and includes a concise statement 'Get word/char/line/paragraph/sentence count and reading time estimate.' It distinguishes itself from sibling tools like text_case or text_lorem, which focus on transformation rather than analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. While the purpose is specific, the description lacks comparison with similar text tools (e.g., text_diff, text_slugify) or conditions under which this tool is preferred.

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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