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check_tells

Read-only

Check text for AI-writing tells (em-dashes, 'not just X but Y', rule-of-three lists, stock vocabulary like delve or seamlessly, hedge words, smart quotes, hidden Unicode) and return a score, each tell with its position, and a cleaned copy. Run it on anything you are about to publish on a human's behalf.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text to check. Free tier: 3,000 chars.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, closed world), so the bar is lower. The description adds real value by disclosing the return shape — a score, each tell with its position, and a cleaned copy — which matters because no output schema exists. It does not mention rate limits or cost behavior beyond the schema's char limit, so not a 5.

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

Conciseness4/5

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

Two sentences, front-loaded with the action and the detection list, followed by the usage trigger. The long parenthetical is justified because it disambiguates what 'tells' means, but it is dense enough to keep this from a clean 5.

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?

A single-parameter, read-only tool with no output schema, and the description steps in to describe the return payload (score, positioned tells, cleaned copy) and the intended usage context. Nothing critical is missing for an agent to invoke it correctly, though the absence of any output schema means more return-detail could have helped.

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% and the single parameter's schema already documents the text input and free-tier 3,000-char limit. The description adds no additional syntax, format, or constraint detail for the parameter, so the baseline of 3 applies.

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?

Specific verb (check) plus resource (text for AI-writing tells) with an enumerated list of the exact patterns detected (em-dashes, 'not just X but Y', rule-of-three, stock vocabulary, hedge words, smart quotes, hidden Unicode). This is far more discriminative than the sibling names (check_ai_crawlers, lint_agent_md) and an agent can tell the tools apart immediately.

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

Usage Guidelines4/5

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

The closing sentence gives a clear trigger: 'Run it on anything you are about to publish on a human's behalf.' That is strong positive guidance for when to use it. There is no explicit when-not or named alternative (e.g., lint_agent_md vs this), so it falls short of a 5.

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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