idea_score

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: scoring across 10 dimensions with a skeptical stance and returning a verdict. However, it lacks details on potential limitations (e.g., accuracy, data sources), error handling, or performance characteristics like rate limits, which would be valuable for an agent to know.

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 front-loaded with the core purpose in the first sentence, followed by specific details on dimensions and verdicts. Every sentence adds value without redundancy, and the structure is clear and efficient, 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 tool's complexity (scoring across 10 dimensions) and the absence of both annotations and an output schema, the description does a good job of explaining what the tool does and what it returns. However, it could be more complete by detailing the output format (e.g., structured scores vs. summary) or potential edge cases, which would help an agent better anticipate results.

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 100%, so the schema already documents both parameters well. The description adds context by explaining that the tool infers from README and project context if 'idea_description' is not provided, which clarifies the parameter's optional nature and default behavior. This goes beyond the schema's technical description, earning a score above the baseline of 3.

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 specific action ('Score your idea across 10 dimensions') and the resource ('idea'), with explicit details on the 10 scoring dimensions and the four possible verdict outcomes. It distinguishes itself from sibling tools like 'coach' or 'review' by focusing on quantitative scoring rather than qualitative feedback or general assistance.

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 ('with a skeptical default stance') and mentions that the tool infers from README/project context if no idea is provided, giving some guidance on when to use it. However, it does not explicitly state when to choose this tool over alternatives like 'coach' or 'review', nor does it provide exclusions or prerequisites for usage.

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