lnkLsOrdJo_search

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it reveals that JSON format is not supported by the API (only HTML/XML), provides specific display recommendations (50-100 for law searches), and explains the tool's specialized purpose. No contradictions with annotations exist.

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 with clear sections (purpose, args, returns, examples). Every sentence adds value: the opening explains the tool's unique purpose, parameter documentation is comprehensive, and examples show practical usage. It could be slightly more concise in the parameter explanations but remains efficient overall.

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 search tool with 9 parameters, 0% schema coverage, no output schema, and annotations covering safety aspects, the description provides excellent context. It explains the tool's specialized linkage purpose, documents all parameters thoroughly, provides format limitations, and includes practical examples. The main gap is lack of output format details, but this is partially mitigated by the type parameter documentation.

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. It provides detailed explanations for all 9 parameters: query purpose, display recommendations with rationale, page numbering, type format limitations with JSON clarification, knd filtering purpose, jo formatting requirements with examples, jobr formatting with examples, sort functionality, and ctx automation. This fully 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 verbs ('searches local ordinance articles that are linked to specific national law articles') and resources ('ordinance articles', 'law articles'). It distinguishes this tool from siblings by explaining it focuses on linkages between ordinances and laws, unlike generic search tools like 'law_search' or 'ord_search'.

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 ('to see which local ordinances implement or relate to specific law provisions'). It includes practical examples showing usage patterns. However, it doesn't explicitly state when NOT to use it or name specific alternative tools from the sibling list for different search needs.

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