memory_semantic_search

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 thoroughly discloses behavioral traits: default content_mode='preview', preview_chars=300, the alias relationship between limit and top_k, the effect of fields on result envelope, and the nuanced follow parameter. It also clarifies that omitting follow is not unfiltered, which prevents misinterpretation.

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 with a high-level purpose line, then a bulleted Args section. It is thorough but slightly verbose (e.g., the follow parameter explanation could be more concise). The front-loading of purpose is effective.

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 complexity (9 parameters, nested objects, output schema exists), the description covers all necessary aspects: return format (envelope vs flat list), content modes, follow lineage, and metadata filters. The output schema already documents return structure, so the description's focus on parameter behavior and result variant is sufficient.

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 input schema provides only names and types. The description compensates fully by detailing all 9 parameters in the Args block, including the meaning of each, defaults, and the alias. This adds essential value 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?

The description starts with 'Perform a semantic search using vector embeddings,' which is a specific verb+resource combination. It clearly distinguishes from sibling tools like memory_list (non-semantic list) and memory_hybrid_search (hybrid approach), as it focuses purely on vector embeddings.

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 context for parameters like content_mode, follow, and fields. It mentions that 'omitting follow is NOT unfiltered' and references memory_list for follow mode documentation. However, it does not explicitly state when to use this tool over alternatives (e.g., memory_hybrid_search), leaving some implicit guidance.

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