recall_context

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 transparently states that the tool surfaces notes/ideas from the knowledge graph, implying a read-only retrieval operation. It also adds the helpful context that it targets forgotten information, giving insight into its purpose and expected output. It does not disclose potential limitations or side effects, but the verb 'surface' suggests no mutation, which is adequately transparent.

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 extremely concise at two sentences, front-loading the use case and action. The first sentence clearly states what the tool does, and the second adds value by explaining the benefit ('connect current work with past knowledge'). Every word earns its place, with no unnecessary detail or repetition.

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?

For a tool with only two simple parameters and no output schema, the description covers the essential context: what it does, when to use it, and the source (knowledge graph). It doesn't describe the return format in detail, but 'surface' implies a list of notes/ideas, which is sufficient given the tool's simplicity. The description also clarifies its role among siblings by emphasizing the writing context.

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 already provides 100% coverage for both parameters (current_text and max_results), so the description does not need to add much. It does not go beyond the schema, though it reinforces the purpose of current_text by tying it to 'while writing'. This matches the baseline of 3 for high schema coverage.

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 uses a specific verb ('surface') and resource ('related notes and ideas from your knowledge graph'), clearly stating the tool's function. It distinguishes itself from siblings by framing the use case explicitly as 'while you are writing', which sets it apart from tools like query_mind or discover_connections. The purpose is immediately clear and actionable.

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 a clear context for when to use the tool: 'While you are writing'. This implies the user is drafting content and needs to recall relevant past knowledge. However, it does not explicitly mention when not to use it or name alternative sibling tools, so it falls short of a 5 but is still well-defined.

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