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Reply to a lead

reply_to_lead

Send a reply in one of the user's lead conversations, exactly as the Reply box on the website does (the other party is notified). Requires the user's confirmation: the first call returns the exact message for them to approve.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lead_idYes
messageYesThe reply text, written or approved by the user.
confirmation_tokenNoLeave empty on the first call: you get an action_summary and a token instead of the action. After the user explicitly confirms that summary, call again with the SAME arguments plus this token.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations: it discloses the external side effect ('the other party is notified'), the mandatory user-confirmation gate, and the exact first-call behavior (returns the message for approval rather than sending). Annotations only flag readOnly=false and openWorld=true, so this adds substantial behavioral context.

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 tight sentences, zero waste. The core action and its side effect come first, and the confirmation requirement follows immediately, so the agent gets the critical behavioral constraint up front.

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?

For a mutation tool with no output schema, the description covers the key risks: external notification and the required confirmation handshake. Minor gaps remain (error behavior, whether retries are safe given idempotentHint=false), but nothing essential to correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%, with confirmation_token already well documented in the schema. The description reinforces the flow semantics ('the first call returns the exact message for them to approve'), clarifying why the token exists and how it relates to user approval, adding meaning beyond the raw parameter list.

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?

States a specific verb and resource ('Send a reply in one of the user's lead conversations') and anchors it to the familiar website Reply box, which lets an agent distinguish it from siblings like get_lead, list_leads, and set_lead_status.

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 conveys that the reply must be user-approved and describes the two-call flow, which implies when to invoke it, but it never names an alternative tool or states when not to use this one (e.g., versus set_lead_status). Usage is implied rather than spelled out.

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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