remember

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the tool's core function (saving for persistence) and typical use cases, but lacks details on implementation specifics like storage limits, retrieval mechanisms, error conditions, or authentication requirements. It adds basic context but leaves significant behavioral aspects undocumented.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second provides usage guidelines. Both sentences earn their place with no wasted words, making it efficient and well-structured for quick understanding.

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 moderate complexity (3 parameters, 1 required), no annotations, 0% schema coverage, but with an output schema present, the description is partially complete. It covers the 'what' and 'when' adequately but lacks details on parameters, behavioral constraints, and error handling. The output schema may help with return values, but the description doesn't fully compensate for the missing annotation and parameter documentation.

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%, so the description must compensate for parameter documentation. It doesn't mention any parameters explicitly, though it implies 'content' through 'piece of knowledge' and hints at organization through 'important decisions, preferences, or facts.' However, it doesn't explain the purpose of 'tags' or 'project' parameters, leaving them undocumented. The description adds minimal semantic value beyond the bare 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?

The description clearly states the tool's purpose: 'Save a piece of knowledge for cross-session persistence.' It specifies the verb ('save') and resource ('knowledge'), but doesn't explicitly differentiate it from sibling tools like 'learn' or 'recall' that might also handle knowledge storage or retrieval.

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?

The description provides clear usage context: 'Use this when the user says 'remember this' or when important decisions, preferences, or facts should be preserved across conversations.' This gives specific triggers and scenarios, though it doesn't explicitly mention when NOT to use it or name alternatives like 'learn' or 'recall' from the sibling list.

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