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pghdma

CallRail MCP

compare_periods

Compare current and previous N-day periods to identify per-company and agency-wide changes in call volume and minutes.

Instructions

Compare current N-day window vs the previous N-day window.

Returns per-company minute / call deltas + agency-wide totals. Useful for "is Malick growing?", "did we lose Stewart traffic this month?", catching invoice surprises before they hit.

Args: days: Window length on each side (default 30 = roughly one cycle). Cap: 365 (don't ask for "5-year delta" — likely a typo). account_id: Auto-resolves if omitted.

Returns: A breakdown showing current vs previous totals, % deltas, and per-company growth/shrink. Sorted by absolute minute change.

Implementation: pulls call data for both windows in one tool call. Tracker counts use current-snapshot for both periods (CallRail doesn't expose historical tracker counts) — only minute deltas reflect actual period-over-period change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
account_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations, so description carries full burden. It discloses implementation detail (one tool call, historical tracker limits) and clarifies which deltas are accurate, which is excellent transparency.

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?

Concise yet comprehensive, with clear sections (purpose, use cases, args, returns, implementation). No superfluous 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?

Given output schema existence, description still covers return breakdown clearly. Fully informs agent of what to expect and caveats, making it highly complete.

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%, but description richly documents both parameters: days (default, cap, typo warning) and account_id (auto-resolve), adding critical context 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?

Purpose is extremely clear: compare current vs previous N-day window with per-company and agency-wide metrics. Specific verbs and resource, distinct from all sibling tools.

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?

Provides explicit use cases like detecting growth or invoice surprises, but does not state when to avoid using it or mention alternatives, though none exist among siblings.

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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