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pghdma

CallRail MCP

list_calls

Retrieve and filter call data with pagination support. Apply filters like date range, source, and answered status to narrow results.

Instructions

List calls. Paginated. Filterable by company, date window, source, answered status.

Args: account_id: Auto-resolves if omitted. company_id: Filter to one company. Omit for all companies. days: Lookback in days (default 7). Ignored if start_date provided. start_date: 'YYYY-MM-DD'. end_date: 'YYYY-MM-DD' (defaults to today). source: Filter (e.g. 'google_paid', 'google_organic', 'direct', 'bing_paid'). answered: 'true' or 'false'. per_page: Max 250. page: 1-indexed. fields: Comma-separated additional fields to include, e.g. 'company_name,source_name,keywords,landing_page_url,device, first_call,value,tags,note,gclid,fbclid,utm_source,utm_medium, utm_campaign,utm_content,utm_term,referrer_domain'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
pageNo
fieldsNo
sourceNo
answeredNo
end_dateNo
per_pageNo
account_idNo
company_idNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses pagination and parameter behaviors (e.g., auto-resolution of account_id, ignoring days if start_date provided). However, it does not mention rate limits, result ordering, or what happens on empty results, leaving some ambiguity.

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?

The description is front-loaded with the main purpose and then provides a clear bullet-like list for each parameter. It is slightly verbose but well-organized, earning its length with useful details.

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?

With 10 parameters and no schema coverage, the description covers all parameters adequately. An output schema exists (not shown), so return value details are less needed. However, it lacks mention of result ordering or limits beyond per_page, and no context on typical use cases.

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 coverage is 0%, so the description must compensate. It does so thoroughly: explains each parameter (e.g., days default 7, ignored if start_date; date format YYYY-MM-DD; source examples; answered 'true'/'false'; per_page max 250; page 1-indexed; fields comma-separated with examples; account_id auto-resolves; company_id filter). This adds significant meaning beyond the schema.

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 clearly states 'List calls' with pagination and filtering options, distinguishing it from sibling tools like get_call or search_calls_by_number. It provides specific filterable attributes (company, date window, source, answered 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 implies usage for listing and filtering calls but does not explicitly state when to use this tool vs alternatives like get_call for a single call or compare_periods for period comparisons. No when-not guidance is given.

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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