run_probe

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

Annotations indicate readOnlyHint=true, and the description aligns by stating it 'surfaces' and 'returns' data. The description adds useful context: the harness doesn't auto-grade because the same model attempts and judges. No 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 consists of two concise sentences, each adding value. No unnecessary words or repetition.

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?

The tool is simple with one input and known output (prompt and grader hint). The description covers purpose, return content, and post-action. An output schema exists but isn't shown; however, the description provides sufficient high-level understanding.

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 schema has one parameter (probe_id) with 0% description coverage. The tool description does not explain the parameter's format or constraints, leaving the agent to infer from context. A simple parameter, but the lack of elaboration is a gap.

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?

Description clearly states it surfaces a registered probe for self-attempt, returning the prompt and grader hint. This distinguishes it from sibling tools like register_probe and record_attempt, which have different purposes.

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 instructs the agent to call record_attempt after attempting, and explains the lack of auto-grading due to the model doing both attempting and judging. This provides clear usage context, though it doesn't explicitly exclude alternative tools.

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