brain_federate

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 explains the core behavior (copying edges and lessons) and includes a dry_run parameter for preview. However, it does not disclose whether the operation is destructive to the source, authentication requirements beyond org-membership, rate limits, or what happens on failure. The absence of output schema means return values are unspecified.

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 front-loaded with the key purpose and includes a concrete example, but it is somewhat verbose with the 'new hire use case' sentence. Every sentence adds value, though the use case could be condensed. Overall, it is well-structured and easy to parse.

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 5 parameters and no output schema, the description is fairly complete but lacks information on the tool's return value (e.g., count of transferred edges, errors). It also does not mention idempotency, partial failures, or post-conditions. The example helps, but an agent would need to infer behavior from the dry_run parameter.

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 100% with all 5 parameters described. The description adds value beyond the schema by providing an example ('min_confidence=0.6'), explaining domain values ('e.g. "billing", "auth", "deploy", "infra". Use "*" for all domains'), and clarifying the instance_id as 'your brain instance ID (destination)'. This helps the agent understand parameter usage.

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 purpose: 'FedBrain Layer 6 — Private org knowledge transfer: copy CKG edges + lessons from a source brain into your brain for a specific domain.' It uses specific verbs ('federate', 'copy') and distinguishes itself from the sibling 'syndicate_search' by contrasting global anonymity with org-privacy.

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 tells when to use this tool ('new hire use case') and when not to use it ('Unlike syndicate_search ... brain_federate is org-private'). It also provides prerequisites: both brains must be in same org or source instance_id explicitly shared. However, it does not differentiate from other siblings like brain_diff or brain_search, which share similar contexts.

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