extract_emailsExtract all email addresses found in a block of free-form text (notes, pasted documents, signatures). Optionally deduplicates and lowercases the results.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Free-form text to scan for email addresses. | |
| lowercase | No | Lowercase all extracted addresses. Default true. | |
| deduplicate | No | Remove duplicate addresses. Default true. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions optional deduplication and lowercasing but omits details about return format, input size limits, or error handling. The agent cannot infer output structure without an output schema.
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?
The description is a single, concise sentence with a parenthetical example and a clear statement of optional features. No wasted words, front-loaded with the main action.
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?
The tool is straightforward with 3 params, but the description lacks return value information (e.g., returns an array of strings). Without an output schema, this is a notable gap. Otherwise adequate for simple extraction.
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 coverage is 100%, so the schema already describes all parameters. The description adds only 'Optionally deduplicates and lowercases' which overlaps with schema defaults. No additional semantic value beyond 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 clearly states 'Extract all email addresses found in a block of free-form text', providing a specific verb and resource. It distinguishes from sibling tools (like verify_email, clean_email_list) which focus on validation or cleaning, not extraction.
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 gives context for when to use the tool (notes, pasted documents, signatures) but does not explicitly exclude alternatives or state when not to use it. The implied usage is clear enough for most scenarios.
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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Each tool has a clearly distinct purpose. Overlaps like verify_batch vs submit_bulk are explicitly differentiated by synchronous vs asynchronous behavior. Extraction, cleaning, verification, and management tools are well-separated.
All tool names follow a consistent verb_noun pattern (e.g., register_account, verify_email, get_job_status). There is no mixing of conventions or vague verbs.
15 tools cover the domain of email verification and account management without redundancy. Each tool fills a specific role—single verification, batch sync, bulk async, job polling, results retrieval, list cleaning, extraction, domain health, credit purchasing, and account management.
The tool set provides complete lifecycle coverage: account registration, usage tracking, credit purchase, email verification (single, batch, bulk with async), job management, list cleaning, email extraction, and domain health checks. No obvious gaps for the intended functionality.