get_scoring_rubric

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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it reads from a YAML file, returns a structured rubric dict, and raises specific exceptions (FileNotFoundError, ValueError). This covers file I/O, output structure, and error conditions without contradictions.

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 appropriately sized and front-loaded, starting with the core purpose, followed by Args, Returns, and Raises sections. Every sentence earns its place by providing essential information without redundancy, structured for quick scanning.

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 tool's moderate complexity (1 parameter, file I/O), no annotations, and an output schema present, the description is complete. It explains the purpose, parameter semantics, return structure, and error handling, compensating for the lack of annotations and low schema coverage effectively.

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 0%, so the description must compensate fully. It adds significant meaning beyond the bare schema by explaining the 'track' parameter's purpose, listing valid enum values (creative-apps, reasoning-agents, enterprise-agents), and linking it to the file path. This provides complete parameter context.

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 purpose with specific verb ('Return') and resource ('scoring rubric for the specified track'), and distinguishes it from siblings by focusing on rubric retrieval rather than submissions, rankings, or scores. It explicitly mentions loading from a specific YAML file path, making the operation concrete.

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 context by specifying the track names and file path, but does not explicitly state when to use this tool versus alternatives like 'list_submissions' or 'get_submission_detail'. It provides clear input requirements but lacks comparative guidance with sibling tools.

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