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extract_codes

Extract OTP codes and verification links from the most recent email in a disposable inbox to complete signup and verification processes.

Instructions

Extract OTP codes and verification links from the most recent email in an inbox. Use this after creating an inbox and receiving a verification/signup email.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inbox_idYesThe inbox ID to extract codes from (uses most recent email)

Implementation Reference

  • Handler implementation for extract_codes tool that calls the blipFetch API.
    async ({ inbox_id }) => {
      const result = await blipFetch(`/v1/inboxes/${inbox_id}/extract`);
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • Tool registration for extract_codes.
    server.tool(
      "extract_codes",
      "Extract OTP codes and verification links from the most recent email in an inbox. Use this after creating an inbox and receiving a verification/signup email.",
      {
        inbox_id: z
          .string()
          .describe("The inbox ID to extract codes from (uses most recent email)"),
      },
      async ({ inbox_id }) => {
        const result = await blipFetch(`/v1/inboxes/${inbox_id}/extract`);
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
Behavior3/5

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

No annotations provided, so description carries full disclosure burden. Successfully clarifies it targets the 'most recent email' and specific content types (OTP codes/links). Missing error handling (no emails found, no codes present) and return format details.

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?

Two sentences with zero waste. Front-loaded with specific action, second sentence provides workflow context. No redundancy with structured fields.

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?

Appropriately complete for a focused single-purpose tool. No output schema exists; description implies extracted content is returned but doesn't specify format (JSON, string, etc.). Sufficient given tool simplicity and clear naming.

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% with complete parameter documentation. Description alludes to 'most recent email' behavior but doesn't add substantial semantic detail beyond what the schema already provides for inbox_id. Baseline 3 appropriate for high-coverage schemas.

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 (extract) + resource (OTP codes and verification links) + scope (most recent email). Clearly distinguishes from sibling 'read_email' by focusing on pattern extraction rather than full content retrieval.

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?

Provides explicit temporal guidance ('Use this after creating an inbox and receiving a verification/signup email') establishing the workflow sequence. Lacks explicit 'when-not' guidance or named alternatives (e.g., vs read_email), but context makes appropriate usage clear.

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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