attribution_health

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

No annotations are provided, so the description carries the full burden. It does disclose one meaningful behavioral constraint: the tool should not invent runtime proof. However, it says nothing about whether the operation is read-only, what side effects exist, what happens with incomplete inputs, or how results are returned.

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 a single sentence that front-loads the main action and includes a concise guardrail. It contains no filler or repetition, though the extreme brevity does contribute to the tool being under-specified overall.

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?

Given two undocumented object parameters, no annotations, no output schema, and a cluster of closely related sibling tools, the description is too thin for an agent to invoke the tool correctly. It explains the purpose but not the input structure, return value, or how it relates to similar tools.

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 input schema has zero description coverage and the two parameters, 'stages' and 'statuses', are both untyped empty objects with no documentation. The description does not mention either parameter or explain what shape the nested objects should take, so it adds no semantic value beyond the schema.

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 states a specific verb ('Score') and a clear resource ('the seven attribution lifecycle stages'), which makes the tool's core purpose understandable. The phrase 'without inventing runtime proof' adds a distinguishing behavior but does not explicitly contrast it with siblings such as validate_attribution_pipeline, so it stops short of full differentiation.

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?

There is no guidance on when to use this tool versus alternatives like validate_attribution_pipeline or detect_attribution_gaps. The description implies it scores existing proof rather than creating it, but it never states explicit conditions, prerequisites, or exclusions.

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