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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds context about data sources (FreeWheel Marketplace, Common Crawl) and the nature of output ('source provenance and confidence scores'), which goes beyond the structured fields. No contradictions found.

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

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

Three well-organized sentences: the first states the core function and data sources, the second defines the audience and goal, and the third summarizes inputs and outputs. No fluff, front-loaded with the most critical information.

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

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

With an output schema present, detailed annotations, and full parameter descriptions, the tool is well-specified. The description provides necessary context about the tool's purpose and data sources. It does not explain MMM signals or the relevance of FreeWheel/Common Crawl, but that is domain knowledge rather than a critical gap.

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

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

Schema coverage is 100% with all six parameters described in detail. The description's mention of 'campaign IDs, date ranges, and channel filters' merely restates what the schema provides, adding no extra meaning. Baseline of 3 is appropriate.

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

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

The description clearly states the tool's primary function: 'Provides unified attribution insights for retail media and programmatic campaigns by analyzing MMM signals from FreeWheel Marketplace and Common Crawl.' It names specific data sources and distinguishes itself from sibling tools like programmatic_attribution_calibrator by focusing on bridging cross-channel gaps.

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

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

The description says it's 'Designed for ad revenue operations teams to bridge cross-channel performance gaps,' giving clear context on when to use the tool. However, it does not explicitly mention alternatives or exclusions, so it earns a 4 rather than 5.

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