scan_anomalies

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

With no annotations, the description carries the full burden. It reveals the multi-step algorithm (overlapping tiles, candidate localization, high-resolution crop verification) and discloses output fields (confidence, angle, silkscreen). This goes beyond a generic 'scan' claim, though it stops short of discussing performance implications or input requirements.

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, dense sentence but remains structured and front-loaded with the primary purpose. It packs substantial detail without excessive verbosity, earning its length through workflow explanation. It could be slightly more scannable, but it is far from bloated.

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 7 parameters and no output schema, the description provides a comprehensive overview: purpose, algorithm, and key output fields. It does not explicitly detail every parameter (e.g., target, max_tiles) but the schema covers those. The algorithm context helps explain why certain parameters exist, making the tool's behavior well-rounded.

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 high (86%), so baseline is 3. The description adds algorithm context that explains the purpose of region, overlap, tile_size, and verify parameters, linking them to the tiling and verification process. This enriches the semantic meaning beyond the schema's individual descriptions.

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?

Description clearly states the tool scans for abnormal/skewed components in images, using a specific verb ('scan') and resource ('abnormal/skewed components'). It distinguishes itself from sibling tools like analyze_image or locate_object by focusing on anomaly detection and describing a tiled verification workflow.

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 implies usage for detecting anomalies in images but does not explicitly instruct when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. Sibling tool names provide context, but the description itself lacks comparative guidance.

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