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pghdma

CallRail MCP

by pghdma

get_lead_timeline

Get a lead's full cross-channel activity timeline: every call, form submission, and text thread from that person in one response, with first-touch/last-touch attribution.

Instructions

Get a lead's full cross-channel activity timeline: every call, form submission, and text thread from that person in one response, with first-touch/last-touch attribution.

This replaces the manual "search calls by number + search forms by email" dance when reconstructing a customer's history.

Args: lead_id: 'PER...' lead id (from list_leads). account_id: Auto-resolves if omitted. per_page: Timeline page size (max 250). page: 1-indexed.

Returns: JSON string with lead (the person record) and timeline[] (chronological interaction entries, paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
lead_idYes
per_pageNo
account_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.4

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility and does so thoroughly: it reveals cross-channel aggregation, first-touch/last-touch attribution, pagination behavior (page and per_page with max 250), account_id auto-resolution, and the exact return structure (JSON string with lead and timeline). This goes well beyond what the schema or annotations would tell an agent.

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?

The description is front-loaded with the core purpose, then provides a short motivation, followed by a compact, structured Args list and a Returns section. Every sentence adds useful information; there is no filler or repetition of schema content.

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?

The definition covers all four parameters, return shape, pagination semantics, and the source of the key identifier. It also explains why the tool exists relative to the manual alternative, which gives an agent enough context to select and invoke it correctly without needing additional documentation.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description compensates fully. It tells the agent that lead_id is the 'PER...' id from list_leads, that account_id auto-resolves when omitted, that per_page is the timeline page size with a 250 maximum, and that page is 1-indexed. This adds meaning far beyond the bare type declarations.

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?

The description opens with a specific verb and resource ('Get a lead's full cross-channel activity timeline') and immediately enumerates the exact data types included: calls, form submissions, and text threads. It also distinguishes itself from sibling tools by explicitly stating it replaces the manual 'search calls by number + search forms by email' workflow.

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?

The description states a clear use case: reconstructing a customer's history across channels, and names the alternative manual approach it replaces. It does not, however, explicitly list when not to use it or compare it to other sibling tools like list_calls or list_form_submissions beyond the one replacement note.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.