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

The description adds behavioral context beyond the annotations by explaining that the model uses 'the asset's full assessment history in context' and returns specific outputs (delta score, defects, wear indicators, recommendations, trajectory). It does not contradict the annotations (readOnlyHint=false, destructiveHint=false) and provides meaningful insight into how the tool operates.

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 two sentences long, with the first sentence front-loading the core purpose and the second efficiently describing the return values and behavioral context. There is no redundant or unnecessary information; every phrase earns its place.

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 no output schema, the description carries the burden of explaining return values, which it does thoroughly (delta score, defects, wear indicators, recommendations, trajectory). It also explains the use of historical context. However, it does not address edge cases (e.g., no previous assessment) or response format specifics, leaving a small gap. Overall, it is nearly complete for a tool of this complexity.

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 description coverage is 100%, so all three parameters are already documented in the input schema. The description adds some contextual relationship (e.g., history context for asset_id) but does not provide additional parameter-level details beyond what the schema offers, resulting in a baseline score of 3.

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 function: 'Run an AI condition assessment of an asset from a photo.' It goes beyond a simple statement by specifying unique outputs like 'Condition Delta Score' and 'degradation trajectory,' which distinguishes it from sibling tools like tascan_condition_history or tascan_recommend_fix.

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 provides clear context for when to use the tool: when you need a photo-based AI condition assessment with historical context. It implies the use case but does not explicitly name alternatives or exclusions, which prevents a 5. However, the context is clear enough for an agent to select it appropriately.

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