list_rules

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

No annotations are provided, so the description carries the full burden. '列出全部' explicitly states the tool lists all rules (read-only, no side effects), and the field list (id, level, auto-fixable, description) tells the agent what to expect in the result. This sufficiently covers behavior for a simple zero-parameter list tool.

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 short sentences with no filler. The first sentence states the core function and output fields; the second provides concrete usage guidance. 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?

For a zero-parameter tool with an output schema, the description is nearly complete: it states scope, returned fields, and a concrete use case. It could have added a note about behavior (e.g., always returns all rules rather than paginated), but given the simple read-only nature and existing output schema, it is sufficiently complete.

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 tool has 0 parameters, so the baseline is 4. The description adds extra context that this tool serves to explain the 'rules' parameter used elsewhere, which is semantically useful beyond the empty schema.

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 uses a specific verb ('列出'/'list') and resource ('全部校对规则'/'all proofreading rules') and enumerates the returned fields (id, level, auto-fixable status, description). This clearly distinguishes it from siblings like check_text, fix_text, and count_text.

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 second sentence gives explicit conditions for use: when you need to know what values the 'rules' parameter accepts or understand a rule's boundaries. It does not name sibling tools or exclusions, but the context is clear enough for an agent to route to this tool versus the siblings.

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