CrashStory MCP

get_review_analytics

Get review velocity analytics for an attorney from their slug, including trends, freshness, momentum, composite score, city percentile, and month-over-month series.

Instructions

Get review velocity analytics for a specific attorney. Includes review frequency trends, freshness score, momentum indicators, composite score, city percentile rank, and month-over-month time series.

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": {
      "slug": "<slug>"
    },
    "name": "get_review_analytics"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	Yes	Canonical attorney slug from search_attorneys (e.g. "levine-law-llc-denver")

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 10, 2026

TDQS

B3.2/5.0

Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It adds valuable detail by enumerating returned metrics (frequency trends, freshness score, momentum indicators, etc.), revealing output behavior. However, it does not mention whether authentication is required, whether data is cached, or any potential side effects, though as a read-only analytics tool the risk is low.

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 two sentences: a clear purpose statement followed by a list of included metrics. Every item in the list is relevant and informative, with no filler. It loses one point because the list is somewhat long, but still highly efficient.

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?

Given the simple input (one required parameter) and absence of an output schema, the description does a good job of setting expectations by listing the analytics components. It could be more complete by noting conditions like 'attorney must have reviews' or how the time series is structured, but it is sufficient for an agent to decide whether this tool fits the user's need.

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?

The input schema already provides a thorough description of the single `slug` parameter with a concrete example ('levine-law-llc-denver'). Since schema description coverage is 100%, the baseline is 3 even though the tool description adds no additional parameter information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Get review velocity analytics for a specific attorney.' It names a specific resource and lists a comprehensive set of included metrics, making the purpose distinct from generic review lookups. However, it does not explicitly differentiate from sibling tools like get_review_intelligence, so it misses the top score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use this tool versus alternatives such as get_review_intelligence or get_attorney_reviews. The description implies usage for review analytics but provides no exclusions, prerequisites, or alternative tool references, leaving the agent without decision support.

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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