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GrowthMCP

GrowthMCP

by Lokeshwar2005
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

build_evidence_packet

Create a compact audit packet linking a business question to source rows and calculations. Ensures traceability for marketing analytics decisions.

Instructions

Create a compact audit packet tying a business question to source rows and calculations.

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": {
      "question": "<question>",
      "records": "<records>"
    },
    "name": "build_evidence_packet"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceNoclient-supplied
recordsYes
questionYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does not say whether the tool persists anything, requires specific permissions, is idempotent, or how 'source' defaults are applied. It only conveys that output is a 'compact audit packet,' leaving key behavioral traits undisclosed.

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?

A single efficient sentence that front-loads the verb and resource with no wasted words. It is well-sized, though the brevity leaves the tool under-explained given its complexity.

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

Completeness2/5

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

An output schema exists so return values need not be described, but with three parameters at 0% schema coverage and no annotations, the description omits too much. An agent lacks the input format and behavioral context needed to invoke it confidently.

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

Parameters2/5

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

With 0% schema description coverage, the description must compensate but largely does not. It loosely maps 'business question' to the question param and hints at records via 'source rows,' but gives no format, structure, or meaning for records, question, or the source parameter's default value.

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 pairs a specific verb (create) with a concrete resource (a compact audit packet) and notes its content (tying a business question to source rows and calculations). This differentiates it from siblings like analyze_growth_query or investigate_campaign without naming them. It is clear, though 'audit packet' remains somewhat abstract.

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 on when to use this tool versus alternatives such as build-adjacent analysis tools (analyze_growth_query, investigate_campaign, normalize_growth_records) or when it should not be used. The audit/packet framing implies a context, but no explicit conditions or alternatives are stated.

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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