zhiji_facts_get

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

No annotations are provided, so the description must convey behavioral traits. It mentions the output includes structured facts with subject attribution, confidence, and conflict status, but does not disclose data freshness, permission requirements, or side effects. For a read-like operation, this is adequate but minimal.

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 consists of two concise sentences: the first states the core function and output format, the second adds usage guidance. Every word serves a purpose with no redundancy or filler.

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 has one optional parameter and no output schema, the description covers the essential purpose, output characteristics, and typical use cases. It could be improved by specifying the exact output structure or data source, but is sufficient for an agent to select and understand the tool.

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 already provides complete coverage for the single parameter 'userEmail' with a description. The tool description adds no additional semantics beyond the schema, meeting the baseline but not exceeding it.

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 retrieves a list of structured facts from conversations, specifying attributes like subject attribution, confidence, and conflict status. It distinguishes itself from narrative memory tools by emphasizing precise facts, and provides concrete use cases (verifying names/dates/quantities). The verb '获取' and resource '结构化事实清单' are specific and unambiguous.

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 indicates scenarios where this tool is suitable (precise fact-checking) and contrasts with narrative memory, implying when not to use it. However, it does not name alternative sibling tools directly (e.g., zhiji_memory_search), leaving the agent to infer the distinction.

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