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

With no annotations, the description carries the full behavioral burden, and it discloses that the tool returns both a result and its legal basis. However, it says nothing about behavior on an invalid or unknown slug, whether args is optional, or any error handling — meaningful gaps for a tool with no annotation coverage.

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?

Three compact sentences, front-loaded with the purpose, with the critical constraint flagged by a ★ marker for scannability. Nothing is obviously wasted, though the example list is slightly verbose.

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 no output schema, the description usefully notes it returns result plus legal basis and explains the cross-tool dependency on list_calculators. It is nearly complete for a calculator runner, lacking only failure-mode guidance.

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?

Schema description coverage is 100%, and the description largely restates what the schema already documents (slug from list_calculators, args keys matching fields). It adds no syntax, format, or example key/value detail beyond the structured field 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+resource ('执行一个法律计算') and its output ('返回计算结果与依据'), then anchors it with concrete example queries (litigation fees, severance multiples, child support). An agent can distinguish this from lookup siblings like sifa_lookup or get_law_article at a glance.

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?

It clearly states the prerequisite workflow: slug must come from list_calculators and args keys must match that tool's fields, plus example questions that show the applicable contexts. It stops short of explicit exclusions or naming which sibling to prefer for non-calculation queries.

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