run_self_distill

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

Beyond the destructiveHint annotation, the description adds that the tool reads logs, detects signals, and persists lessons, with dryRun option to avoid persistence. 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?

Two sentences: first states purpose, second details actions. Efficient and front-loaded with no redundant content.

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?

Covers key aspects (automated, no human feedback, persistence). Could mention retrieval of lessons, but not necessary given sibling tools like search_lessons exist.

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 covers all parameters; description adds meaning (dryRun prevents persistence, model requires ANTHROPIC_API_KEY), enhancing agent understanding beyond the schema.

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 runs a self-distillation agent to auto-evaluate sessions and generate improvement lessons, differentiating it from siblings like infer_lesson_from_history or retrieve_lessons by emphasizing no human feedback.

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 implicitly indicates use when automated lesson extraction is desired without human input. It lacks explicit when-not or alternative mentions but is clear enough for an agent to infer context from sibling tools.

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