record_thinking_event

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

No annotations provided, so description bears full burden. States it writes to a table but does not disclose idempotency, concurrency, permission requirements, or potential side effects. Adequate for a straightforward log action but lacks detail.

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?

Compact and front-loaded with clear purpose, but uses Python docstring Args format which may not be ideal for all agents. Every sentence is informative with 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 5 parameters, 1 required, and no annotations, the description covers event types and parameter details. Output schema exists so return value documentation is not required; lacks examples or edge case handling but sufficient for the tool's simplicity.

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?

With 0% schema coverage, description fully compensates by explaining each parameter: event_type (with enumerated list), source_type, optional content_id, agent_slug for specific events, and context. Adds meaning beyond schema types and defaults.

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?

Clearly states it logs a preference signal to a specific table. Distinguished from sibling logging tools by focusing on thinking profile events with specific event types like brainstorm_acted_on and idea_rated_high.

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 explicit guidance on when to use this tool versus alternatives like log_agent_run or record_research_finding. The list of event types implies usage scenarios but does not provide when-not or comparative context.

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