mimic_ai_knowledge_write

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

Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds that the tool lets Mimic learn across builds, but does not disclose potential failures, permissions, or side effects beyond what annotations cover. With annotations providing the safety profile, the description adds moderate context.

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 concise with two sentences and a brief params summary. It front-loads the purpose and usage guidance without redundancy. Every sentence adds value.

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 there is no output schema, the description is complete. It explains the tool's purpose, usage guidelines, and parameter details. Annotations provide idempotence and non-destructive hints, making the description sufficient for an agent to invoke the tool correctly.

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 descriptions for all parameters. The description adds extra meaning for the 'type' parameter by providing use cases and examples (e.g., 'rule' for design rules), which goes beyond the schema enum list. The 'id' and 'data' parameters are clear from schema but not further elaborated.

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 that the tool saves knowledge entries (component recipe, layout pattern, DS gap, or design rule) to a persistent store. It uses a specific verb (saves) and resource (knowledge store), and distinguishes itself from the sibling mimic_ai_knowledge_read tool.

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 provides explicit guidance on when to use the 'rule' type (user correcting build behavior in a generalizable way) and notes that other types are usually written automatically. It does not explicitly state when not to use the tool, but the guidance is clear enough.

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