lnkLs_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 and idempotency. The description adds valuable behavioral context beyond annotations: it notes that JSON is not supported by the API (only HTML/XML), provides a recommendation for display count (50-100 for law searches), and mentions that 'ctx' is injected automatically. No contradiction with annotations exists.

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: purpose statement first, usage context second, followed by detailed parameter explanations and an example. Every sentence earns its place by providing essential information without redundancy. The example is concise and illustrative.

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), the description is largely complete. It covers purpose, usage, all parameters with semantics, and includes an example. However, it doesn't detail the return structure beyond 'Search results with linked laws list or error', which could be more specific (e.g., format of results). With no output schema, this leaves some ambiguity.

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 fully compensates by explaining all parameters in the 'Args' section. It adds meaning beyond the schema: default values, constraints (max 100 for display), recommendations (50-100 for law searches), format options (HTML/XML, JSON not supported), sort order details, and automatic injection of 'ctx'. The only minor gap is that 'oc' is described only as 'Optional OC override (defaults to env var)', which is somewhat vague.

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: 'searches Korean laws that have linkages to local ordinances.' It specifies both the verb ('searches') and the resource ('laws linked to local ordinances'), and distinguishes it from siblings by focusing on law-ordinance linkages rather than general law searches (e.g., law_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: 'Useful for understanding how national laws relate to local regulations.' This indicates when to use it (for law-ordinance linkage analysis). However, it doesn't explicitly state when not to use it or name specific alternatives among the many sibling tools, which would be needed for a score of 5.

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