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

Beyond the annotations, the description discloses important behavior: evidence_note and stance should be reported separately, disclaimers must be preserved, and if no edge exists the agent should say so rather than fabricating evidence. It also explicitly notes read-only behavior and no external calls, which reinforces the annotation profile.

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 dense but well organized, leading with purpose, then alternatives, then parameter semantics, then behavioral caveats. It is slightly longer than strictly necessary, but every section earns its place and the arrow/bullet formatting makes it easy to scan.

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 tool with an output schema and strong annotations, the description covers all decision-relevant aspects: when to use it, what the parameters mean, what to do when the relation is unknown, what to report, and how to handle missing edges. Nothing needed for correct invocation is missing.

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?

Although schema coverage is 100%, the description adds crucial semantics: from and to are concept names, not sentences; relation is a graph edge type; it lists the allowed relation values (causes, enables, requires, contrasts); and clarifies that all three are required. This goes well beyond the schema's minimal 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 states a specific verb and resource: it confirms the evidence for one causal edge ('A가 B를 유발한다는 한 연결의 근거를 확인한다'). It further sharpens the scope by saying the tool targets 'an edge you already know,' which clearly sets it apart from path-finding or explanation tools.

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 says when to use it, provides sibling alternatives (path_between, answer_why, k_snippets), and states when to switch to path_between if the relation is unknown. This is exemplary guidance for an agent selecting among related tools.

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