Portrait identification

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real value beyond that by defining what min_score means behaviorally — 'similarity floor below which the portrait counts as unknown' — telling the agent how low-confidence results are reported, and by enumerating accepted input encodings.

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?

One front-loaded sentence states the purpose, then a compact Args block gives exactly the per-parameter detail the schema lacks. No repetition of schema types, no filler, nothing an agent must scan past.

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 three-parameter read-only tool with an output schema (so return values need no explanation), the description covers inputs and the unknown-result rule adequately. It stops short of explaining how multiple images are batched in the response or the ordering/size of the candidate list, which would fully close the loop.

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 0%, so the description must carry the burden and it does: images accepts a file path, base64 raw bytes, or a data URI; top_k is candidates per portrait bounded 1-10; min_score is a 0-1 similarity floor. Every parameter gains syntax or range meaning beyond the bare schema types.

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?

States a specific verb and resource — identifying which characters appear in cropped portrait images — which is concrete enough to act on. It does not distinguish itself from the sibling tools character_match or character_lookup, which an agent might plausibly confuse with identification, so it falls short of a 5.

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 phrase 'cropped portrait images' implicitly scopes the input (cropped portraits, not full art or free-form images), which is useful implied usage guidance. However there is no explicit when-to-use versus character_match/character_lookup, no prerequisites, and no stated exclusions.

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