lnkDep_search

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety aspects. The description adds valuable behavioral context beyond annotations: it specifies response format limitations ('JSON not supported by API'), provides practical recommendations ('Recommend 50-100 for law searches to ensure exact matches are found'), and notes automatic parameter injection ('ctx: MCP context (injected automatically)').

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 well-structured and front-loaded with the core purpose, followed by organized sections for Args, Returns, and Examples. Every sentence earns its place by providing essential information without redundancy. The bullet-point style in the Args section enhances readability while maintaining efficiency.

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's complexity (6 parameters, 0% schema coverage, no output schema) and the absence of output schema, the description provides complete context. It covers purpose, all parameters with semantics, behavioral constraints, format limitations, practical recommendations, and includes a concrete example. The annotations provide safety context, and the description fills all remaining gaps effectively.

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?

With 0% schema description coverage, the description carries the full burden of parameter documentation and excels at it. It provides detailed semantics for all parameters: explains 'org' is a ministry/department code with example, specifies 'display' range and recommendation, clarifies 'page' is 1-based, explains 'oc' defaults to env var, details 'type' options and limitations, mentions 'sort' exists, and notes 'ctx' is automatic. This comprehensively compensates for the schema gap.

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's purpose with specific verb ('searches') and resource ('local ordinances linked to laws managed by a specific government ministry or department'). It distinguishes from siblings by focusing on ministry-specific ordinance links, unlike other tools like 'law_search' or 'eflaw_search' that appear to search different legal domains.

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 provides clear context for when to use this tool ('searches local ordinances linked to laws managed by a specific government ministry or department'), but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. The example shows a typical usage scenario, which helps guide implementation.

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