validate_with_models

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

Annotations already provide destructiveHint=true and openWorldHint=true. The description adds the workflow pattern (starts jobs, poll vs collect) and the exclusion of llm_job_* tools, which is useful context beyond annotations. However, it does not elaborate on side effects or required permissions.

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?

Single sentence that is front-loaded with action ('Ask...'), no redundant words, and efficiently conveys core information.

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?

While no output schema exists, the description directs to other tools for result collection, which is acceptable. It covers the job lifecycle. However, it omits explanation of the judgeModel parameter and does not define what 'validation' entails, leaving some gaps for a tool with 4 parameters.

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 coverage is 100% with all parameters documented. The description implicitly references the 'models' parameter ('two or more provider CLIs') but adds no additional meaning beyond the schema descriptions. Baseline score of 3 is appropriate.

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 verb 'ask' and resource 'two or more provider CLIs to independently validate a question'. It distinguishes from siblings like ask_model (single model) and compare_answers (comparison of existing answers) by specifying multi-provider validation and job polling workflow.

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?

Explicitly tells when to use this tool (to start multi-model validation jobs) and directs to specific polling/collection tools (job_status, job_result) while explicitly excluding llm_job_* tools. This provides clear usage context and alternatives.

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