zerodom_find

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

With no annotations provided, the description carries the full burden. It discloses the search behavior (case-insensitive substring match on label and type), implying a non-destructive read operation. It also mentions performance characteristics (three lines vs full graph). It doesn't explicitly state that it doesn't modify anything, but the search nature is clear. It doesn't cover error conditions or return format, but those are covered by the output schema. Overall, it's transparent enough.

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?

Two sentences with no waste. The first sentence states the core purpose; the second provides usage guidance and cost comparison. The most important information (what it does) is front-loaded. Every word 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?

Given the tool's simplicity (one parameter), the presence of an output schema, and the sibling differentiation, the description is complete. It explains the search criteria, matching behavior, and usage context. The agent has enough information to invoke it correctly. The output schema handles return values, so nothing else is needed.

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 single parameter 'query' has 0% schema description coverage, so the description must compensate. It explains that the query is a substring used for case-insensitive matching on node labels and types. This adds semantic meaning beyond the schema's name/type, telling the agent exactly what the query affects. It could be more detailed (e.g., whether regex is supported), but it sufficiently clarifies the parameter's role.

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 states a clear verb ('Search'), a specific resource ('current page's graph'), and the action (matching nodes by query). It also distinguishes itself from siblings by explicitly advising to prefer this over re-reading the whole page, and it names the sibling alternative implicitly. This is specific and actionable.

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 gives explicit when-to-use guidance: 'Prefer this over re-reading the whole page when you already know what you are looking for.' It contrasts the cost of this tool ('three lines') with the full graph read, making the decision clear. It doesn't explicitly list when-not-to-use cases, but the positive guidance is strong.

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