Open-Brain

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'graph traversal' and 'LLM gap-filling sub-queries,' which hint at complex processing and potential latency or resource usage, but doesn't detail specific behaviors like error handling, rate limits, or output format. For a tool with no annotations, this is inadequate.

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 highly concise and front-loaded, consisting of two sentences that efficiently convey the tool's purpose and usage. Every sentence adds value without redundancy, making it easy to parse quickly.

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 implied by 'multi-hop retrieval' and 'graph traversal,' and with no annotations or output schema, the description is incomplete. It lacks details on what the tool returns, how it handles errors, or any performance considerations. For a potentially complex tool, this leaves significant gaps in understanding.

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?

The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't mention any parameters, which is appropriate here. Since there are no parameters, the baseline is 4, as the description doesn't need to compensate for missing param info.

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 performs 'multi-hop retrieval with graph traversal + LLM gap-filling sub-queries,' which specifies the verb (retrieval with traversal and gap-filling) and resource (implicitly knowledge/data). It distinguishes from siblings by mentioning 'bridging topics and multi-session synthesis,' though not explicitly naming alternatives. However, it lacks a direct resource reference, making it slightly vague.

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 on when to use this tool: 'Best for bridging topics and multi-session synthesis.' This implies it's suited for complex queries requiring connections across topics or sessions. It doesn't explicitly state when not to use it or name alternative tools, but the guidance is sufficient for basic differentiation.

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