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extract_emails

Extract email addresses

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesInput text

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / properties / args
      Removed value: -{
-  "description": "Tool arguments",
-  "properties": {
-    "text": {
-      "description": "Primary input text",
-      "type": "string"
-    }
-  },
-  "type": "object"
-}
    • addedInput schema / properties / text
      Added value: +{
+  "description": "Input text",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[]New value: +[
+  "text"
+]
  2. Added

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only states the action without mentioning output format, handling of duplicates, or any edge cases, leaving the agent to infer behavior.

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?

The description is extremely concise at four words and front-loads the key verb and object. It is appropriately sized for a simple tool, though a slightly more detailed description could improve clarity without becoming verbose.

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

Completeness2/5

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

For a tool with a single parameter and no output schema, the description does not specify the return type or how emails are extracted (e.g., regex behavior). The completeness is insufficient for an agent to fully understand what will be returned.

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?

The schema covers the single parameter 'text' with description 'Input text', achieving 100% coverage. The tool description adds no new meaning beyond the schema; it simply states the overall purpose, which is already implied by the parameter name and description.

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 'Extract email addresses' uses a specific verb ('extract') and resource ('email addresses'), clearly distinguishing it from sibling tools like extract_phones and extract_links. The purpose is unambiguous.

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?

The description implies usage when one needs to extract email addresses from text, but it does not explicitly state alternatives or when-not conditions. No exclusions or comparisons to sibling extraction tools are provided.

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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