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

The description discloses that the connections are AI-synthesized hypotheses ('AI 합성') and indicates a sorting/limit behavior ('8개 정렬'). This goes beyond typical annotations. However, it doesn't mention output format, error cases, or side effects, and no annotations are provided to cover the rest.

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 very concise (one short sentence), but the phrasing is ambiguous, especially '8개 정렬'. It's under-specified rather than efficiently clear, sacrificing clarity for brevity.

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?

With no output schema or annotations, the description must carry the full burden. It provides a rough idea of the return (AI-synthesized hypotheses, 8 sorted) but lacks detail about the response structure, fields, pagination, or error behavior. Given the low complexity, it barely meets minimum viability.

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 schema has a single parameter 'entity_id' with no description, and the description only implies it refers to the entity in question via 'Entity의'. This adds minimal meaning; it doesn't specify the ID format, type of entities, or how it's used beyond being the source entity.

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 that the tool gets causal hypotheses between an entity and other entities, which is a specific verb+resource. It distinguishes itself from siblings like get_entity or search_alpha by focusing on connections. However, the phrase '8개 정렬' is ambiguous and not fully clear, so it's not a perfect 5.

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?

There is no guidance on when to use this tool versus alternatives. No exclusions, prerequisites, or alternative tool mentions. The description only implies it should be used to fetch connections for an entity.

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