recall_best_solution

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

With no annotations, the description fully discloses behavioral traits: returns most recent successful lesson with confidence indicator, explains badge meanings for staleness, and reveals a side effect (resetting confidence clock to 1.0). This exceeds expectations for transparency.

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?

Description is appropriately sized: first sentence states purpose, second gives usage guidance, third details return value and badges, fourth notes side effect, and ends with an example. Every sentence earns its place without 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 no output schema, the description adequately explains return content (lesson with confidence, badges) and side effect. Could be slightly more precise about return format, but the example helps. Comparable sibling tools exist, but the description is sufficient for its complexity.

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% and both parameters are well-described. Description adds value with an example and reinforces partial match support but does not introduce new semantic meaning 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?

Description clearly states the tool recalls best known solutions from past lessons with a specific verb (Recall) and resource (best known solution). It differentiates by explicitly advising to call it before tasks that might have been done before, which distinguishes it from sibling tools like recall_context.

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?

Provides explicit guidance on when to use: 'Call this BEFORE attempting any task that might have been done before.' While not specifying when not to use, the context effectively implies the alternative is to proceed without prior knowledge.

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