plausible-mcp

Compare Periods

compare_periods

Read-onlyIdempotent

Compare metrics between two date ranges side by side, ideal for before/after deploy analysis, returning aggregate values for each period plus delta (absolute and %).

Instructions

Compare metrics between two date ranges side by side. Ideal for before/after deploy analysis. Returns aggregate values for each period plus the delta (absolute and %).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "site_id": "<site_id>",
      "period_a": "<period_a>",
      "period_b": "<period_b>"
    },
    "name": "compare_periods"
  }
}

Input Schema

Name	Required	Description
`goal`	No	Filter by goal name (e.g. Signup, Purchase)
`page`	No	Filter by page path. Exact match by default, use * as trailing wildcard (e.g. /blog*)
`metrics`	No	Metrics to return. Defaults vary by tool.
`site_id`	Yes	Plausible site domain (e.g. example.com). Required.
`period_a`	Yes	First date range, e.g. "2024-01-01,2024-01-07" or "7d"
`period_b`	Yes	Second date range, e.g. "2024-01-08,2024-01-14" or "7d"
`property_filters`	No	Filter results by built-in dimensions or custom event properties, e.g. [{ "property": "visit:channel", "operator": "is", "values": ["Organic Search"] }] or [{ "property": "plan", "values": ["pro"] }]. Entries are combined with AND.

Output Schema

Name	Required	Description
`deltas`	Yes	Per-metric change from period_a to period_b (absolute and percent)
`period_a`	Yes
`period_b`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.8.0Sep 28, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered structurally. The description adds useful behavioral context by specifying the return semantics ('aggregate values for each period plus the delta (absolute and %)'). It does not contradict the annotations, but it omits nuances like metric defaulting or how filters are combined, which the schema covers.

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 short sentences with zero filler. The core purpose is front-loaded, the use case follows, and the return format closes it. Every sentence earns its place.

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

Completeness3/5

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

For a 7-parameter tool with 100% schema coverage, an output schema, and rich annotations, the description adequately conveys the essential scope, use case, and return format. However, it does not mention the optional filter (property_filters) or metric defaulting behavior, leaving the agent dependent on the schema for those details — reasonable, but slightly short of fully self-sufficient.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description reinforces the core parameters by mentioning 'two date ranges' (period_a/period_b) and 'metrics', and maps naturally to those fields. It adds little beyond the schema, which is acceptable given the schema's completeness.

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 states a specific verb ('Compare'), a specific resource ('metrics between two date ranges'), and the side-by-side comparison framing that distinguishes it from siblings (get_timeseries, get_breakdown, get_conversions). It also names the return shape (aggregate values plus delta), so an agent can identify this tool without opening the schema.

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 gives an explicit use case ('Ideal for before/after deploy analysis') that helps an agent decide when to invoke it. However, it does not name the sibling tools or state when NOT to use it (e.g., for time-series trends or single-period breakdowns), leaving the differentiation to inference from tool names rather than explicit routing guidance.

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

Deploy Server