recall

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: natural-language search, filtering by multiple dimensions (tier, type, tags, etc.), temporal filters, knowledge graph connections, and scope control. It does not describe the return format or pagination behavior, but the output schema exists to cover that.

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 well-structured: starts with purpose, then usage guidance, then query examples, then enumerates filters. Every sentence adds value. It is somewhat lengthy but justified by the parameter richness. No superfluous content.

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 29 parameters, no schema descriptions, no annotations, and 45 sibling tools, the description provides a comprehensive overview of functionality. It covers the primary use case, filtering options, and special features (graph_depth, scope). It does not detail the output schema but that exists separately.

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 description coverage, the description must add meaning. It lists filter categories and temporal filters but does not explain all 29 parameters individually. It provides enough context for common use cases but leaves some parameters (e.g., 'session_id', 'include_session_context') without explanation.

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 begins with a clear verb+resource: 'Search for relevant memories from past experience.' It further distinguishes itself by specifying natural-language search and providing query examples, which sets it apart from sibling tools like 'search' or 'get_memories' that may have different search semantics.

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 explicitly states 'USE THIS WHEN' followed by concrete scenarios (solving problems, debugging errors, design decisions) and provides good/bad query examples. It does not explicitly mention when not to use or list alternatives, but the context is sufficiently clear for an agent to make appropriate selections.

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