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Funkel AI

get_lead

Read-onlyIdempotent

Return full detail for a single lead by id, INCLUDING the derived reply_state and opt_out flags. Always call this before drafting or sending a message — a lead whose reply_state is 'replied', 'rejected', or 'opted_out', or whose opt_out is true, must NEVER be drafted to or messaged. Use source='approved' for leads in active campaigns; default 'discovered' is for agent-found leads awaiting approval.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoLead source. Default 'discovered'.
lead_idYesLead id (from a prior find_leads result) (UUID format, e.g. 550e8400-e29b-41d4-a716-446655440000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety of the call itself is covered. The description adds genuinely new context: the tool returns derived flags and acts as a gate that must precede any messaging. It stops short of describing error behavior (e.g. unknown lead_id) or the full response shape, so not a 5.

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?

Three sentences, front-loaded with what is returned, then the safety-critical invariant, then parameter routing. The long em-dash sentence earns its length by encoding a hard precondition, and there is no filler.

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

Completeness5/5

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

No output schema exists, and the description compensates by naming the key derived fields returned. With only two parameters, full schema coverage, and rich annotations, an agent has everything needed to call this correctly and safely.

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 100%, so the baseline is 3, but the description earns an extra point by giving operational meaning to source beyond the schema's terse 'Lead source. Default discovered.': approved maps to active campaigns and discovered to leads awaiting approval.

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 ('Return full detail for a single lead by id') and names the derived fields it surfaces (reply_state, opt_out). This clearly separates it from find_leads and search_external_leads, which locate leads rather than return one lead's full state.

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?

Explicitly mandates when to use it: 'Always call this before drafting or sending a message', plus when-not conditions tied to reply_state/opt_out values. It also routes the source parameter to the right scenario (approved = active campaigns, discovered = pending agent-found leads).

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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