memory_find_duplicates

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

No annotations are provided, so the description fully discloses behavior: scanning cross-references, similarity threshold, optional LLM comparison, rate limiting (120s cooldown). It also describes the return structure in detail.

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-organized: a concise summary, process explanation, parameter list, return dictionary, and rate limit note. Every sentence adds value without redundancy.

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 complexity and lack of annotations, the description covers all necessary aspects: purpose, parameters, return values, rate limiting, and alignment with UI. It is comprehensive.

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 coverage is 0%, so the description explains all four parameters with defaults and added context, e.g., max_similarity is for backward compatibility, use_llm controls semantic comparison. This goes well 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 explicitly states the tool's purpose: 'Find potential duplicate memory pairs with optional LLM-powered comparison.' It specifies the mechanism (scans cross-references, similarity threshold), and distinguishes it by mentioning alignment with graph UI duplicate detection.

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, such as default threshold and optional LLM use. It mentions alignment with UI but does not explicitly state when not to use this tool or suggest alternatives among siblings like memory_merge.

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