mimir_synthesize

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

Annotations already declare destructiveHint=true. The description adds that the tool creates entities linked to a journal entry, implying state mutation. But it does not detail the extent of destruction (e.g., whether prior entities are overwritten) or other side effects beyond creation.

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 (4 sentences) and front-loads the core purpose. Every sentence adds value: describing the action, the output structure, a prerequisite, and the broader goal. No redundancy.

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 the tool's complexity (4 params, output schema exists), the description covers the synthesis process and prerequisite. It does not need to explain return values due to output schema. Minor gap: no mention of error conditions or performance implications.

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 each parameter having a description. The description adds minimal extra meaning beyond listing the lesson types and mention of tags/session_id/visibility in context, but does not significantly enhance parameter understanding.

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 performs 'session synthesis' and extracts specific structured lessons (success, failure, correction, dead_end, decision). It distinguishes itself from sibling tools like mimir_ask or mimir_ingest by focusing on post-session analysis and entity creation.

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?

It mentions the prerequisite 'Requires --llm-endpoint to be configured' and positions the tool as an 'overnight synthesis loop for agent self-improvement', implying a use case. However, it lacks explicit when-not-to-use or alternatives, leaving interpretation open.

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