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analyze_distinct_words

Read-only

Count distinct words in text and display their frequency to analyze vocabulary usage and identify recurring terms.

Instructions

Count distinct words in text and show their frequency

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to analyze for distinct words
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds that it 'shows their frequency' which provides some behavioral context about the output format, but doesn't specify whether it returns a sorted list, raw counts, or other details about the analysis behavior.

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

Conciseness5/5

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

The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple analysis tool and front-loads the core functionality.

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

Completeness3/5

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

For a simple read-only analysis tool with good annotations and complete schema coverage, the description is adequate but minimal. It doesn't explain the output format (no output schema exists) or edge cases like how punctuation, case sensitivity, or stop words are handled, which would be helpful context.

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 description coverage is 100% with the single 'text' parameter well-documented in the schema. The description mentions 'text' implicitly but adds no additional semantic context beyond what the schema already provides about the input requirements.

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?

The description clearly states the specific action ('Count distinct words'), the resource ('text'), and the output ('show their frequency'). It distinguishes from sibling tools like 'analyze_text_stats' by focusing specifically on word frequency analysis rather than general text statistics.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'analyze_text_stats' or other text analysis tools. It doesn't mention prerequisites, limitations, or typical use cases for word frequency analysis.

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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