get_confidence_scores

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but does not cover critical aspects like whether it's a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., list of scores, JSON structure). This leaves significant gaps for agent understanding.

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, clear sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and efficiently communicates the core function, making it easy for an agent to parse quickly.

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 the complexity of structure prediction tools and the lack of annotations and output schema, the description is insufficient. It does not explain return values (e.g., format of confidence scores), error conditions, or behavioral traits, leaving the agent with incomplete information for proper tool invocation and result interpretation.

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 100% description coverage, clearly documenting both parameters (uniprotId and threshold). The description does not add any additional meaning beyond the schema, such as explaining residue-level details or threshold implications. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 action ('Get') and target ('per-residue confidence scores for a structure prediction'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'analyze_confidence_regions' or 'validate_structure_quality', which might also involve confidence metrics, so it lacks sibling distinction.

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 no guidance on when to use this tool versus alternatives. With siblings such as 'analyze_confidence_regions' and 'validate_structure_quality' that may relate to confidence, there is no indication of specific use cases, exclusions, or prerequisites, leaving the agent without contextual direction.

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