list_learnings

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only indicates a read operation ('Lists') without detailing output format, ordering, pagination, or any side effects. The phrase 'from past experiences' adds limited context but does not explain what 'learnings' entail or how they are retrieved.

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, clear sentence with no redundant information. It is well-structured and front-loaded with the core purpose, making it easy to parse quickly.

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?

The description is adequate for a simple list tool but lacks clarity on its specific role among many sibling tools and does not explain expected return value or filtering behavior beyond the schema. Given the absence of an output schema, some additional context would be beneficial, but the tool's simplicity prevents this from being a critical gap.

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?

The input schema describes the single parameter 'tags' as 'Filter by tags (optional)', giving 100% schema coverage. The description itself adds no additional meaning to the parameter, so a baseline score of 3 is appropriate.

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 states a clear action ('Lists') and resource ('learnings from past experiences'), which conveys the tool's basic purpose. However, it does not differentiate it from sibling tools like 'get_similar_learnings', which also deals with learnings but has a different retrieval focus.

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?

There is no guidance on when to use this tool versus alternatives such as 'get_similar_learnings' or 'list_patterns'. The description does not mention any specific contexts, exclusions, or prerequisites, leaving the agent without sufficient direction for tool selection.

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