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LexLink-ko-mcp

LexLink-ko-mcp

by joohyukjung
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

chain_law_system

Read-onlyIdempotent

Trace a law's full hierarchy from parent statute to delegated decrees, administrative rules, and linked ordinances. Clarifies subordinate connections.

Instructions

Map the full law system hierarchy (법령 체계 조회).

Chains: law search → delegation tree → related admin rules → linked ordinances. Shows how a law connects to its subordinate regulations.

Args: law_name: Law name (e.g., "건축법", "근로기준법") oc: Optional OC override type: Response format

Returns: Law hierarchy: parent law, delegated decrees/rules, linked ordinances

Examples: >>> chain_law_system(law_name="건축법") >>> chain_law_system(law_name="개인정보 보호법")

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "law_name": "<law_name>"
    },
    "name": "chain_law_system"
  }
}

Input Schema

NameRequiredDescriptionDefault
ocNo
typeNoJSON
law_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A4.2/5.0
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, so the description doesn't need to repeat that. The description adds valuable behavioral context beyond annotations by revealing that the tool performs a multi-step chain (law search → delegation tree → related admin rules → linked ordinances) and returns a structured hierarchy. This informs the agent about potential complexity and the nature of the result, which is beyond what annotations provide.

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

Conciseness5/5

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

The description is excellently structured: it opens with a one-line purpose, then a chain breakdown, followed by Args, Returns, and Examples. Every sentence earns its place, with no redundancy or filler. It is concise yet comprehensive, using bullet-like formatting that is easy to parse.

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?

The tool has a moderate complexity (chaining multiple lookups) and no output schema. The description covers the purpose, the chain process, each parameter, the return structure, and provides multiple examples. This is nearly complete. However, it lacks details on edge cases (e.g., what if a law has no subordinate regulations) and does not clarify how this tool relates to sibling chain tools like chain_full_research, which would enhance completeness.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It does provide an Args block that explains each parameter: law_name with examples, oc as 'Optional OC override', and type as 'Response format'. This adds some meaning beyond the bare schema, but 'OC override' is cryptic and 'Response format' is vague without enumerating allowed values. The examples help for law_name, but the overall parameter semantics are only partially clarified.

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 tool's purpose with a specific verb 'Map' and a concrete resource: the full law system hierarchy. It further breaks down the chain steps (law search → delegation tree → related admin rules → linked ordinances), which distinguishes it from sibling chain tools like chain_amendment_track or chain_dispute_prep. This is a specific, non-tautological statement that tells the agent exactly what the tool does.

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

Usage Guidelines4/5

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

The description implies a clear use case: 'Shows how a law connects to its subordinate regulations.' This provides clear context for when to use the tool. However, it does not explicitly exclude alternative tools or name them as alternatives, which would have pushed the score to 5. It is more than just implied usage because the chain description signals its unique role among related tools.

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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