set_design_context

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

No annotations provided; the description fails to disclose behavioral traits such as whether the tool overwrites previous context, is idempotent, or has side effects. This is a significant gap for a mutation tool.

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 a single sentence, concise and front-loaded with the key action, though it could benefit from bullet points or explicit parameter mapping.

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?

With 6 parameters, no output schema, and no annotations, the description is incomplete. It does not mention return value, idempotency, or expected usage patterns, leaving significant gaps for an AI agent.

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 description coverage is 0%; the description lists example facts (rise times, clocks, etc.) but does not explain the exact format or constraints for parameters like connector_nets (array of what?) or target_impedances (object structure).

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 action ('provide facts') and the resource (design context to sharpen review). It implicitly distinguishes from review tools by focusing on setting context rather than performing the review itself.

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?

No guidance on when to use this tool versus siblings like review_design or review_topic. The description only says 'to sharpen the review' but lacks explicit when-to-use or alternatives.

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