recall_across_lineage

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

Without annotations, the description carries the full burden of disclosing behavioral traits. The verb 'Read' clearly indicates a non-mutating, safe operation, which is useful. However, it does not disclose any caveats such as how missing or invalid dataset_urns are handled, rate limits, or authentication requirements. The description is adequate for a simple read tool but lacks depth.

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 a single, tightly constructed sentence that front-loads the verb and resource. Every word adds value, with no redundancy or tangential information. This is an excellent example of concise, structured documentation.

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 simple tool design (one parameter, output schema present), the description is largely complete for invocation purposes. It states what the tool does and hints at the parameter's meaning. However, it omits any guidance on error behavior or edge cases (e.g., what if some urns do not exist), which would have made it fully comprehensive. The presence of an output schema reduces the need to explain return values, so a 4 is appropriate.

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 compensate for parameter explanations. It clarifies that dataset_urns refers to 'several assets' and gives a lineage path example, but the relationship between 'lineage path' and the array-of-strings schema is ambiguous. It does not explicitly explain the format or expected values of the dataset_urns entries, so it only partially compensates for the missing schema descriptions.

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 clearly states the tool's function with a specific verb ('Read'), resource ('Nightshift memory'), and scope ('several assets at once'), along with a concrete example ('a lineage path'). This effectively distinguishes it from sibling tools like recall_incident_memory, which focuses on incident-specific memory.

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 when to use the tool ('for several assets at once, e.g. a lineage path'), implying it is appropriate for batch reads across a lineage. However, it does not explicitly mention alternatives or exclusions (e.g., 'use recall_incident_memory for single incidents'), so it falls short of a perfect score.

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