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detect_attribution_gaps

Detect attribution lifecycle gaps in your project, uncover unproven stages, and ensure complete tracking coverage.

Instructions

Find unproven or missing attribution lifecycle stages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
evidenceNo
frameworkNo
packageJsonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.1/5.0
Behavior2/5

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

With no annotations, the description must disclose behavior, but it only says 'find', implying a read-only analysis. It does not state whether it modifies anything, what it returns, or how it interacts with the provided files/evidence/packageJson. The behavioral surface is underspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, but it is under-specified rather than appropriately concise. It delivers a single clause without structure or emphasis, and the lack of parameter context makes it feel incomplete rather than economical.

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

Completeness1/5

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

For a tool with four parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain the input semantics, expected output, or how it relates to other attribution tools. An agent cannot reliably use this tool from the description alone.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must explain the four parameters, but it mentions none. The agent has no idea what 'files', 'evidence', 'framework', or 'packageJson' mean for this tool, nor how they affect the search for gaps.

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

Purpose3/5

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

The description states a clear verb ('Find') and resource ('unproven or missing attribution lifecycle stages'), but it is vague about what constitutes a lifecycle stage and how this differs from siblings like validate_attribution_pipeline or diagnose_missing_click_ids. It does not reference the inputs (files, evidence, framework) that would clarify its scope.

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?

No guidance is provided on when to use this tool versus the many related siblings. There are no exclusions, prerequisites, or context cues. An agent would have to guess which tool fits a given scenario.

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