Skip to main content
Glama

다이어그램 그리기

velog_render_diagram

Render architecture and flow diagrams to PNG, upload to Velog, and return markdown for embedding. Auto-checks layout issues before publishing.

Instructions

구성도·흐름도를 그려 PNG 로 만들고 벨로그에 올린다. 본문에 붙일 마크다운을 돌려준다. 좌표만 주면 나머지는 렌더러가 맞춘다 — 노드 폭·캔버스 크기·선 꺾임·라벨 위치는 브라우저 실측으로 정해지고, 글자 삐져나옴/선 관통/겹침은 자가감사가 잡는다. 감사에 걸리면 올리지 않고 무엇이 문제인지 알려준다. 이 판단은 끌 수 없고, 감사에 걸린 산출물은 velog_upload_image 로도 받지 않는다. 고쳐서 다시 그릴 것. 아이콘: alert arrow bell bolt branch browser cache chart check clock cloud code cross database file gear key layers lock mail mobile network package retry search server terminal user 톤: slate gray blue green amber yellow purple teal rose indigo

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
altNo이미지 대체 텍스트
edgesNo
nodesYes
titleYes그림 제목 (좌상단)
groupsNo
legendNo
planesNo흐름 종류. 생략하면 요청/외부 호출/데이터/관측 4종
uploadNo
post_idNo붙일 글 id. 주면 벨로그가 내 글인지 확인한 뒤 받는다
subtitleNo한 줄 설명·근거
Behavior5/5

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

The description discloses key behaviors: automatic layout via browser measurement, self-audit for overflow/overlap/line intersection, audit failure prevents upload and reports issues, the audit cannot be disabled, and failed outputs are rejected even by velog_upload_image. This goes well beyond the annotations (readOnlyHint=false, idempotentHint=false, destructiveHint=false) and adds critical operational context.

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 front-loaded with the core action, followed by behavioral details and reference lists. Each sentence contributes meaningful information, and the icon/tone lists are compact. No redundancy or filler.

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

Completeness5/5

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

For a complex tool with no output schema, the description covers the complete workflow (draw → audit → upload → return markdown), the audit enforcement, and the relationship with velog_upload_image. The schema covers individual parameters, so the description does not need to repeat them. It leaves little doubt about what the tool does and its key failure mode.

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 coverage is 50%, so the description should compensate for undocumented parameters. It adds contextual meaning (coordinates drive layout, node width auto-measured) and lists icon/tone options. However, it does not explain groups, legend, planes, or upload/post_id behavior beyond what the schema already provides. The schema's own field descriptions are quite detailed, so the description adds moderate value.

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 explicitly states the tool draws composition/flow diagrams, renders to PNG, uploads to Velog, and returns markdown for the body. This clearly distinguishes it from sibling tools like velog_render_cover and velog_upload_image.

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 for diagram generation but does not explicitly mention when to use it over alternatives. The note that audited outputs are not accepted by velog_upload_image is an indirect exclusion, but there is no clear when-not or alternative selection guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/milcho0604/velog-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server