score_solution

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 mentions that 'The LLM should evaluate the solution content against the consistency check description and provide an objective score,' which hints at an evaluation process, but doesn't disclose critical behavioral traits such as whether this is a read-only operation, if it modifies data, what permissions are required, or how the scoring interacts with other tools. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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, with the core purpose stated in the first sentence. It uses three sentences efficiently: the first defines the tool, the second provides usage context and score range, and the third adds behavioral guidance. There's minimal waste, though the third sentence could be more integrated for slightly better flow.

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 (a scoring tool with 4 parameters), no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and usage but lacks details on behavioral aspects, return values, or how it fits with sibling tools. For a tool that likely involves evaluation logic, more context on the scoring process or output expectations would improve completeness, but it's adequate as a minimum viable description.

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, with clear documentation for all parameters (solutionId, checkId, score, reasoning). The description adds minimal value beyond the schema: it reinforces the score range (0.0 to 1.0) and mentions 'objective score,' but doesn't provide additional semantics like examples or context for the IDs. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

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: 'Score a solution against a specific consistency check' and 'evaluate how well a solution performs against each consistency check.' It specifies the verb ('score', 'evaluate') and resource ('solution', 'consistency check'), but doesn't explicitly differentiate from sibling tools like 'add_solution' or 'evolve_generation', which appear to be related but distinct operations.

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 implied usage context: 'Use this tool to evaluate how well a solution performs against each consistency check.' It suggests when to use it (for scoring solutions against checks) but doesn't explicitly state when not to use it or mention alternatives among the sibling tools, leaving some ambiguity about its specific role in the workflow.

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