find_attribution_gaps

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 explicitly labels the tool 'Read-only' and explains that it requires no brand list or domain knowledge. However, it does not describe the output format or scanning limitations (e.g., max columns/values), leaving some behavioral details undisclosed.

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?

The description is front-loaded with 'detector' and uses a compact explanatory example. The final sentence 'The high-value data-integrity guarantee' is promotional rather than informative, but overall the text is appropriately sized.

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?

For a tool with no output schema and no annotations, the description should explain what the agent can expect to receive for human review; 'so a human can review them' is vague. It adequately conveys the core concept but leaves out parameter interplay and result shape.

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?

The schema already describes three of four parameters, and the description adds no details about sessionId, maxColumns, anchorMeasure, or maxValuesPerColumn. 'No brand list... needed' reassures about prerequisites, but it does not compensate for the undocumented sessionId or explain how parameters affect cluster detection.

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 identifies the tool as a detector for silently incomplete reports, specifically clusters of dimension members under one attribute value with zero fact rows. It states the verb 'Finds those clusters automatically' and distinguishes it from general find/quality tools by targeting mis-attribution and over-scoped fact exclusions.

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?

It provides a clear heuristic: a single member with no data can be normal, but a whole group under an attribute value signals systematic exclusion, which tells an agent when to use this tool. It does not explicitly name alternatives or exclusions, but the context is strong enough to select it over siblings like find_unused or quality_gate.

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