find_entities

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

No annotations exist, so the description carries the behavioral disclosure burden. It establishes a read-only operation via 'Find' and documents the return dict fields, which is useful. However, it does not disclose how the limit interacts with 'all', what a blank entity_type returns, or any ordering/pagination behavior, leaving those to schema defaults.

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 one concise sentence: scope prefix, action, resource, and return format. It is front-loaded, contains no filler, and does not redundantly repeat parameter details already present in the schema. Every part earns its place.

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 simple tool with two optional parameters and no output schema, the description covers the main call contract and the return keys. It does not specify the behavior when entity_type is omitted or how the limit affects the 'all' claim, but the input schema covers defaults and allowed values. These are minor gaps for a tool of this complexity.

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 100% with both parameters documented, so the baseline is 3. The description's mention of entity_type in the return dict slightly reinforces the filter parameter but adds no new semantic detail about parameter usage. No compensation is needed beyond the baseline.

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 the specific verb 'Find' with the resource 'entity-typed memories in Qdrant' and states the exact return shape. The 'Knowledge Graph' prefix and focus on entity types distinguish it from generic memory siblings like recall and get_related. This is a clear, unambiguous purpose statement.

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 implies that this tool is for retrieving entity-typed memories but gives no explicit when-to-use guidance or alternatives. It does not name siblings such as recall or graph_traverse, so an agent must infer the right routing from the 'entity-typed' qualifier. This meets the implied-usage bar but leaves selection to judgment.

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