Token导航 LogoToken导航TokenDH.com
研究检索external-servicegithub未标认证来源可访问许可证需确认审计通过

fossflow-diagrams福斯流程图

Agent Skill

fossflow-diagrams 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

235

周安装

10

GitHub Stars

公开资料未说明

下载量

82
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:fossflow-diagrams(福斯流程图)
来源仓库:https://github.com/corploc/skills
仓库路径:skills/fossflow-diagrams
安装命令:
npx skills add https://github.com/corploc/skills --skill fossflow-diagrams
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/corploc/skills --skill fossflow-diagrams

简介

fossflow-diagrams 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用该技能。
  • 安装前需确认权限范围、维护状态及是否触发联网或命令执行。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

FossFLOW Isometric Diagrams

Overview

Generate isometric architecture diagrams using the FossFLOW/Isoflow compact JSON format. This format uses minified keys for token efficiency while producing valid importable diagrams.

Iron Rule: The compact format structure defined in llm-generation-guide.md (in this skill directory) is the ONLY valid output format. No variations, no "improved" formats, no object-based alternatives. The exact structure must be respected at all costs.

Canonical reference: https://raw.githubusercontent.com/stan-smith/FossFLOW/refs/heads/master/LLM-GENERATION-GUIDE.md

When to Use

  • User asks for an architecture diagram, infrastructure diagram, or system topology
  • User mentions FossFLOW, Isoflow, or isometric diagrams
  • User wants to visualize cloud infrastructure (AWS, Azure, GCP)
  • User wants to visualize Kubernetes deployments
  • User wants a visual representation of microservices, data pipelines, or any system architecture

When NOT to use: For UML diagrams, sequence diagrams, flowcharts, or non-isometric visualizations (use Mermaid or PlantUML instead).

The Compact Format - MANDATORY Structure

{
  "t": "Title (max 40 chars)",
  "i": [
    ["Item Name (max 30)", "icon_id", "Description (max 100)"]
  ],
  "v": [
    [
      [[itemIndex, x, y], ...],
      [[fromIndex, toIndex], ...]
    ]
  ],
  "_": { "f": "compact", "v": "1.0" }
}

Keys Explained

KeyMeaningTypeConstraint
tTitlestringmax 40 chars
iItemsarray of 3-element arrays["name", "icon", "desc"]
vViewsarray of [positions, connections]Usually 1 view
_MetadataobjectExactly {"f": "compact", "v": "1.0"}

Items (i) - Each item is a 3-element array

["Display Name", "icon_id", "Brief description"]
     ^max 30        ^valid      ^max 100

Views (v) - Each view is a 2-element array

[
  [[0, x0, y0], [1, x1, y1], ...],   // positions: [itemIndex, x, y]
  [[0, 1], [1, 2], ...]               // connections: [fromIndex, toIndex]
]

Red Flags - STOP and Fix

If you catch yourself doing ANY of these, delete and start over:

  • Using object syntax for items ({id:..., type:...}) instead of arrays
  • Using string references in connections ("from": "lb-1") instead of integer indices
  • Adding keys not in the spec (version, components, connections at root)
  • Putting positions inside item definitions instead of in the views array
  • Using 3D coordinates [x, y, z] - positions are [itemIndex, x, y]
  • Inventing icon names not in the valid icons list
  • Omitting the _ metadata field
  • Using "v": "1.0" without the enclosing "_": {"f": "compact",...}

Valid Icons - Quick Reference

Generic (Isoflow collection)

storage server user cloud network security api queue cache function mobile web email analytics backup load-balancer cdn vpn firewall monitor

AWS (prefix: aws-)

aws-ec2 aws-s3 aws-rds aws-lambda aws-api-gateway aws-cloudfront aws-route-53 aws-vpc aws-elb aws-iam aws-cloudwatch aws-sns aws-sqs aws-dynamodb aws-elasticsearch aws-redshift aws-kinesis aws-eks aws-fargate aws-cognito

Azure (prefix: azure-)

azure-virtual-machine azure-storage-account azure-sql-database azure-app-service azure-function-app azure-api-management azure-cdn azure-dns azure-load-balancer azure-active-directory azure-monitor azure-service-bus azure-cosmos-db azure-redis-cache azure-kubernetes-service azure-container-instances azure-logic-apps azure-data-factory azure-key-vault azure-cognitive-services

GCP (prefix: gcp-)

gcp-compute-engine gcp-cloud-storage gcp-cloud-sql gcp-app-engine gcp-cloud-functions gcp-api-gateway gcp-cloud-cdn gcp-cloud-dns gcp-cloud-load-balancing gcp-identity-access-management gcp-cloud-monitoring gcp-cloud-pub-sub gcp-cloud-firestore gcp-memorystore gcp-kubernetes-engine gcp-cloud-run gcp-cloud-workflows gcp-cloud-dataflow gcp-secret-manager gcp-ai-platform

Kubernetes (prefix: k8s-)

k8s-pod k8s-service k8s-deployment k8s-configmap k8s-secret k8s-ingress k8s-namespace k8s-node k8s-persistent-volume k8s-daemonset k8s-statefulset k8s-job k8s-cronjob k8s-hpa k8s-rbac

For the complete icon list (320 AWS, 369 Azure, 280 GCP, 56 K8s icons), see llm-generation-guide.md in this skill directory.

Positioning Guidelines

  • Grid coordinates: X (horizontal), Y (vertical)
  • Negative X = left, positive X = right
  • Negative Y = up, positive Y = down
  • Range: -20 to +20 for both axes
  • Spacing: 3-5 units between components
  • Start main components near (0, 0)
  • Arrange in logical flow (left-to-right or top-to-bottom)

Connection Patterns

PatternExampleUse For
Linear[0,1], [1,2], [2,3]Data pipelines, request flow
Hub & spoke[0,1], [0,2], [0,3]Load balancer, API gateway
Mesh[0,1], [1,0], [1,2], [2,1]Microservices communication
Layered[0,3], [1,3], [2,3]Multiple services to shared DB

Generation Workflow

  1. Identify components from the user's description
  2. Map each to a valid icon (use cloud-specific icons when platform is specified)
  3. Build items array with concise names and descriptions
  4. Calculate positions using grid layout with 3-5 unit spacing
  5. Define connections based on data/control flow
  6. Validate against the checklist below
  7. Output raw JSON (no markdown code fences unless explicitly asked)

Validation Checklist (Run Before Output)

  • Root keys are exactly t, i, v, _ (no extras)
  • _ is exactly {"f": "compact", "v": "1.0"}
  • Each item in i is a 3-element array [name, icon, description]
  • All icon names are from the valid icons list
  • Item names <= 30 chars, descriptions <= 100 chars, title <= 40 chars
  • v contains at least one view: [[positions], [connections]]
  • Each position is [itemIndex, x, y] with valid item index
  • Each connection is [fromIndex, toIndex] with valid item indices
  • Coordinates are within -20 to +20
  • Number of positions matches number of items
  • JSON is valid (no trailing commas, proper quoting)

Common Mistakes

MistakeWrongCorrect
Object items{"name": "DB", "icon": "storage"}["DB", "storage", "Main database"]
String connections{"from": "lb", "to": "svc1"}[0, 1]
Wrong root keys"title", "components""t", "i"
3D positions[0, 5, 3, 0][0, 5, 3] (index, x, y)
Missing metadata(omitted)"_": {"f": "compact", "v": "1.0"}
Invented icons"database", "microservice""storage", "server"
Positions in items["DB", "storage", "desc", 5, 3]Items are 3 elements; positions go in v

Complete Example

Microservices with load balancer, 3 services, message queue, and database:

{
  "t": "Microservices Architecture",
  "i": [
    ["Load Balancer", "load-balancer", "Distributes incoming traffic"],
    ["User Service", "server", "Handles user management"],
    ["Order Service", "server", "Processes orders"],
    ["Payment Service", "server", "Payment processing"],
    ["Message Queue", "queue", "Async communication between services"],
    ["Shared Database", "storage", "PostgreSQL shared data store"]
  ],
  "v": [
    [
      [[0, 0, -6], [1, -6, 0], [2, 0, 0], [3, 6, 0], [4, 0, 6], [5, 0, 10]],
      [[0, 1], [0, 2], [0, 3], [1, 4], [2, 4], [3, 4], [1, 5], [2, 5], [3, 5]]
    ]
  ],
  "_": { "f": "compact", "v": "1.0" }
}

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.26%
按下载量换算29

Claude

28.93%
按下载量换算24

Cursor

22.09%
按下载量换算18

Gemini CLI

10.8%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills