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1Lookup

Confirm the connection

confirm_connection
Idempotent

Confirms the 1Lookup connection works and records which AI assistant connected and when, so the user's 1Lookup API & MCP page can show it as connected. The first confirmation through a connection also tells the 1Lookup team that it works. Use it when the user asks to confirm, check or test their 1Lookup connection. Free, spends no credits. Idempotent: repeat calls simply refresh the record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentNoYour name in any form, e.g. claude, chatgpt, grok, cursor. Normalized to a short lowercase identifier and echoed back.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentYesThe normalized assistant identifier that was recorded
connectedYesThe connection works and was recorded
connected_atYesISO 8601 time of the first confirmation through this connection
first_confirmationYesTrue when this call was the first confirmation for this connection

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Adds real behavioral context beyond annotations: what the call records (assistant name + timestamp), the side effect of surfacing on the user's API/MCP page, and notifying the 1Lookup team on first confirmation. Idempotency is stated both in annotations and here. Slightly redundant on the idempotent point but otherwise rich.

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?

Front-loads what the tool does, then usage guidance, then cost/idempotency. Mostly tight, though the 'tells the 1Lookup team' detail is somewhat tangential and could be trimmed.

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?

Output schema exists, so return values needn't be explained. Description covers purpose, trigger, cost, and idempotency. A note on whether auth/connection setup is prerequisite would complete it, but the core guidance is present.

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%, and the single 'agent' parameter is fully documented in the schema (format, normalization, echo behavior). The description adds nothing about the parameter, so the baseline 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?

Names a specific action (confirms the 1Lookup connection) plus the side effect (records which AI assistant connected and when). This is clearly distinguishable from siblings like verify_email, validate_phone, or ip_lookup.

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

Usage Guidelines5/5

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

Explicit trigger condition: 'Use it when the user asks to confirm, check or test their 1Lookup connection.' Also states the cost (free, no credits) and idempotency, giving the agent enough to decide against alternatives.

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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