validate_plan_quality

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it returns a quality score, issues list, and a 'ready_for_cheap_model' flag, which adds context beyond basic validation. However, it lacks details on error handling, rate limits, or authentication needs, which are important for a tool with no annotation coverage.

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. The 'Args' and 'Returns' sections are structured clearly, but the note about 'cheaper models require stricter plan quality' could be integrated more smoothly. Overall, it's efficient with minimal waste, though minor improvements in flow could elevate it to a 5.

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 (2 parameters, no annotations, but with an output schema), the description is fairly complete. It explains the purpose, parameters, and return values, and the output schema likely covers return details, so the description doesn't need to elaborate further. However, it could benefit from more context on how validation works or links to sibling tools, keeping it from a perfect score.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'plan' is 'The plan text to validate' and 'target_model' specifies the model that will implement, with options like 'haiku|flash|cheap|capable' and the note that 'cheaper models require stricter plan quality.' This compensates well for the schema's lack of descriptions, though it doesn't detail all possible enum values or constraints.

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: 'Validate a plan for implementation by a less capable model.' It specifies the verb ('validate') and resource ('plan'), and distinguishes it from siblings like 'validate_code_quality' by focusing on plan validation rather than code. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_verification_checklist'), so it falls short of a perfect score.

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 mentioning 'less capable model' and that 'cheaper models require stricter plan quality,' which suggests when to use it based on target model constraints. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_quality_standards' or 'suggest_tools,' nor does it provide exclusions or prerequisites, leaving some ambiguity.

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