Skip to main content
Glama
EricSeokgon

egovframe-scaffold-mcp

by EricSeokgon

AGENTS.md 생성

generate_agents_md
Destructive

Diagnoses an eGovFrame project to generate an AGENTS.md file for AI coding tools, documenting build/test commands, RTE version, DbType, rules, and available MCP tools.

Instructions

프로젝트를 진단해 AI 코딩 도구(Claude Code·Copilot·Cursor 등)용 AGENTS.md 를 생성합니다 — 빌드·테스트 명령(래퍼 감지), RTE 버전과 5.x 전환 상태, DbType, 기본 패키지·설정 디렉터리, 설치 공통컴포넌트(매니페스트 관리 여부), 지켜야 할 규칙(좌표·백업 디렉터리·비밀 정보·의존성 기준), 사용할 수 있는 MCP 도구. 기존 파일은 overwrite=true 가 아니면 거부하고, dryRun=true 면 내용만 돌려줍니다. 한국어(기본)·영어.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNo문서 언어ko
dryRunNotrue 면 파일을 쓰지 않고 내용만 반환
fileNameNo파일명(프로젝트 루트 기준, 기본 AGENTS.md — CLAUDE.md 등으로 바꿀 수 있음)AGENTS.md
overwriteNo기존 파일 덮어쓰기(transaction, 실패 시 원복)
projectDirYes대상 프로젝트 디렉터리(절대경로 권장)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.36.1

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false and idempotentHint=false, so the safety profile is known. The description adds genuine behavioral detail beyond that: an existing file is refused unless overwrite=true, and dryRun=true returns content without writing. It does not describe the response shape, but for a mutation tool this is solid added context.

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?

Purpose is front-loaded and the enumerated content is a legitimate, information-dense list rather than filler. It is a single long sentence, but every clause carries meaning, so size is justified by the tool's breadth.

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?

For a mutating generator with no output schema, the description covers what is generated, the overwrite guard, the dry-run mode and the language choice. The main omission is any indication of what the returned value contains in dryRun mode, but overall an agent has enough to call it correctly.

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 100%, so the schema already documents projectDir, overwrite, dryRun, fileName and lang. The description adds only marginal meaning (default Korean with English option) and never mentions fileName or projectDir. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb (generate) and resource (AGENTS.md) and enumerates the exact content it will produce (build/test commands, RTE version, DbType, package/config dirs, MCP tools). It is clearly distinguishable from siblings like generate_egovframe_config or diagnose_egovframe_project without opening any schema.

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 the use case ('for AI coding tools such as Claude Code, Copilot, Cursor'), which gives context, but it never states when to choose this over siblings such as diagnose_egovframe_project or generate_egovframe_report, nor any prerequisites. Usage is inferable rather than explicit.

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