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rabqatab

LexLink

drlaw_search

Read-onlyIdempotent

Retrieve statistical information about how national laws are linked to local ordinances in Korea. Returns HTML visualization of law-ordinance linkage statistics.

Instructions

Retrieve law-ordinance linkage statistics (법령-자치법규 연계현황 조회).

This tool retrieves statistical information about how national laws are linked to local ordinances. Returns HTML visualization/dashboard.

⚠️ Note: This API only supports HTML output format (no XML/JSON). Response schema is not documented by the API provider.

Args: oc: Optional OC override (defaults to env var) ctx: MCP context (injected automatically)

Returns: HTML response with linkage statistics or error

Examples: Get linkage statistics: >>> drlaw_search()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ocNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing safety. The description adds valuable context beyond annotations: it warns about HTML-only output format, notes the response schema is undocumented, and describes what the tool returns ('HTML visualization/dashboard' with statistics or error). This provides important behavioral details not captured in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, warning, args, returns, examples) and avoids redundancy. Every sentence adds value, though the warning about HTML-only format could be integrated more smoothly rather than as a separate warning block.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (statistical retrieval with HTML output), no output schema, and rich annotations, the description is mostly complete. It covers purpose, parameters, returns, and limitations. The main gap is lack of guidance on when to use versus sibling tools, but otherwise provides sufficient context for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and only 1 parameter, the description compensates well. It explains the 'oc' parameter as an 'Optional OC override (defaults to env var)' and clarifies 'ctx' is injected automatically. This adds meaningful semantics beyond the bare schema, though it doesn't explain what 'OC' stands for or when to override it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('retrieve statistical information'), resource ('law-ordinance linkage statistics'), and output format ('HTML visualization/dashboard'). It distinguishes itself from sibling tools by focusing on linkage statistics rather than general law searches or other specialized functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when statistical information about law-ordinance linkages is needed, but provides no explicit guidance on when to use this tool versus alternatives like 'law_search' or 'lnkLs_search'. The examples section shows basic usage but doesn't address decision criteria.

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

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