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review_plan

Review building layouts against Korean building codes to identify violations in lighting, ventilation, egress, and area requirements.

Instructions

평면도·배치도를 건축 법규 관점에서 검토한다 — 채광·환기·피난·면적 요건 위반을 짚는다. 사용자가 도면을 공유하거나 공간 구성 검토를 요청하면 이 도구를 쓴다. 이미지가 아니라 도면에서 읽어낸 구조를 넣는다: 방(용도·외부창 유무)·인접·개구부·동선. 위반(violation) 항목은 답변에서 빼지 않는다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roomsYesParsed rooms with id, use, ext_windows, optional area/floor/access/shape.
openingsNoOpenings, including exterior windows and doors, as parsed objects or pairs.
adjacencyNoRoom adjacency pairs such as [[a,b]] or objects with from/to.
site_scopeNoOptional site scope such as climate/culture/epoch/tech_level.
circulationNoCirculation edges or ordered paths, e.g. [[from,to]] or [a,b,c].
jurisdictionNoOptional jurisdiction key such as KR-서울 for NormClause lookup.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the input must be parsed structural data, not an image, and guarantees that violations are not omitted from the answer. However, it does not explain how missing data is handled, whether jurisdiction influences the review, or what kind of output format to expect beyond the output schema.

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?

Three dense sentences deliver the core action, trigger condition, input semantics, and an output guarantee. There is no fluff or repetition of schema details, and the most important information is front-loaded.

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 output schema and complete parameter descriptions, the definition adequately covers what the tool does, when to use it, what to pass in, and how it behaves. The main gaps are the lack of exclusions/alternatives and jurisdiction-related caveats, but these are minor given the structured schema coverage.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaning by explaining that rooms, adjacencies, openings, and circulation should be the structure extracted from drawings—and clarifies room attributes like use and exterior-window presence—going slightly beyond the schema's generic descriptions.

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 states a specific verb and resource: it reviews floor plans/layouts from a building-code perspective and flags daylight, ventilation, evacuation, and area violations. This clearly distinguishes it from the sibling tools, which focus on paths, comparisons, evidence, or enumeration.

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?

It explicitly says to use this tool when the user shares drawings or requests spatial-composition review. It does not state exclusions or name alternatives, but the trigger condition is clear and actionable.

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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