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business-blueprint商业蓝图

Agent Skill

business-blueprint 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

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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

MIT-0

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:business-blueprint(商业蓝图)
来源仓库:https://github.com/kaisersong/business-blueprint
安装命令:
openclaw skills install business-blueprint
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install business-blueprint

简介

将售前需求转化为可编辑的业务能力蓝图与泳道流程图文档。

  • 适用于解决方案设计、流程梳理与客户协同共创会议支持。
  • 输出标准化模板便于后续开发与测试用例对齐参考。business-blueprint 属于运维类 Skill,可作为该场景下的辅助能力补充。
  • 原始材料质量直接影响蓝图准确性,需确保输入信息完整真实。
  • 建议团队共同审阅初稿后再进入实施阶段,避免理解偏差。

SKILL.md

name
kai-business-blueprint
description
Use when turning presales requirements, meeting notes, or solution materials into editable business capability blueprints, swimlane flows, and application architecture diagrams. Use when generating blueprint JSON, static HTML viewers, or exporting to SVG, draw.io, Excalidraw, or Mermaid formats. When no standard export template applies, default to free-flow output.

Business Blueprint Skill

Use the Python scripts in this repository as the execution surface.

Output Directory

All generated files (blueprint JSON, viewers, exports) go into projects/workspace/ — not the repository root.

python scripts/business_blueprint/cli.py --plan projects/workspace/solution.blueprint.json --from "..."
python scripts/business_blueprint/cli.py --project projects/workspace/solution.blueprint.json
python scripts/business_blueprint/cli.py --export projects/workspace/solution.blueprint.json

Industry Selection

Choose --industry from exactly one of: "common", "finance", "manufacturing", "retail". Select the closest match based on the user's domain and materials; do not invent other values.

IndustryHints content
commonNo hints — generic domains
financeRisk control, credit, compliance, customer profile, etc.
manufacturingProduction planning, quality, warehouse, supply chain, etc.
retailStore operations, membership, POS, order fulfillment, etc.

How to Generate a Blueprint

The AI agent is responsible for entity extraction. The Python tool handles JSON writing, visualization, and export.

Step 1: Read industry hints

Read the seed template at business_blueprint/templates/{industry}/seed.json and get the industryHints.checklist.

Step 2: Extract entities from source text

Using the user's source material AND the industry hints checklist, extract:

  • capabilities: business capability areas (name, description)
  • actors: roles/people involved (name)
  • flowSteps: business process steps (name, actorId, capabilityIds, stepType)
  • systems: IT systems that support capabilities

- See references/entities-schema.md for all entity field definitions - See references/systems-schema.md for systems category/layer rules - See scripts/business_blueprint/templates/common/seed.json for field examples

Step 3: Write the blueprint JSON

Write the JSON file directly to the output path. Use this schema:

{
  "version": "1.0",
  "meta": {
    "title": "...",
    "industry": "retail",
    "revisionId": "rev-YYYYMMDD-NN",
    "parentRevisionId": null,
    "lastModifiedAt": "ISO8601",
    "lastModifiedBy": "ai"
  },
  "context": {
    "goals": [],
    "scope": [],
    "assumptions": [],
    "constraints": [],
    "sourceRefs": [{"type": "inline-text", "excerpt": "..."}],
    "clarifyRequests": [],
    "clarifications": []
  },
  "library": {
    "capabilities": [
      {"id": "cap-xxx", "name": "...", "level": 1, "description": "...", "ownerActorIds": [], "supportingSystemIds": []}
    ],
    "actors": [
      {"id": "actor-xxx", "name": "..."}
    ],
    "flowSteps": [
      {"id": "flow-xxx", "name": "...", "actorId": "actor-xxx", "capabilityIds": ["cap-xxx"], "systemIds": [], "stepType": "task", "inputRefs": [], "outputRefs": []}
    ],
    "systems": [
      {"id": "sys-xxx", "kind": "system", "name": "...", "aliases": [], "description": "...", "resolution": {"status": "canonical", "canonicalName": "..."}, "capabilityIds": ["cap-xxx"]}
    ]
  },
  "relations": [
    {"id": "rel-xxx", "type": "supports", "from": "sys-xxx", "to": "cap-xxx", "label": "支撑"}
  ],
  "views": [],
  "editor": {"fieldLocks": {}, "theme": "enterprise-default"},
  "artifacts": {}
}

Step 4: Generate visualizations

python scripts/business_blueprint/cli.py --export <blueprint.json>

This generates SVG + HTML viewer by default. Use --format drawio|excalidraw|mermaid for other formats.

Export View Selection Policy

Treat export view choice as a routing decision, not a styling preference.

  • If a request matches a supported, standard export template, use that template.
  • If there is no standard export template for the requested diagram, fall back to freeflow.
  • Do not substitute swimlane, matrix, product tree, or other generic views just because they are available.
  • When embedding a blueprint diagram into a report or ad hoc analysis, freeflow is the safe default unless the user explicitly asks for a supported standard template.

Step 5: Generate downstream projection

python scripts/business_blueprint/cli.py --project <blueprint.json>

This generates solution.projection.json, the canonical machine projection consumed by downstream report/slide workflows.

Workflow Decision Tree

User provides raw requirements / meeting notes?
  → AI agent reads hints, extracts entities, writes blueprint JSON
  → Optionally run --project for downstream machine handoff
  → Then run --export for visualization

User needs diagram files (SVG, draw.io, etc.)?
  → --export (default: SVG + HTML viewer)

User unsure about blueprint quality?
  → --validate

User wants downstream report / slide generation?
  → --project

Commands

CommandDescription
--plan <path> --from <text>Generate empty blueprint JSON from source text (AI should prefer writing JSON directly)
--project <path>Generate canonical projection JSON for downstream skills
--export <path>Export SVG + HTML viewer (default), or use --format for other formats
--validate <path>Validate a blueprint and print JSON results

Execution: Run directly as scripts:

python scripts/business_blueprint/cli.py --plan ...
python scripts/business_blueprint/cli.py --export ...

Export Formats

FormatFileUse Case
svg (default)solution.exports/solution.svg + HTML viewerQuick preview, embedding
drawiosolution.exports/solution.drawioEditable diagrams
excalidrawsolution.exports/solution.excalidrawWhiteboard-style diagrams
mermaidsolution.exports/solution.mermaid.mdGitHub-native rendering

Collaboration Boundary

This skill produces semantic intermediate artifacts. Downstream skills consume them:

  • report-creator consumes solution.projection.json → assembles reports
  • slide-creator consumes solution.projection.json → assembles presentations
  • Other skills may consume relations → generate PlantUML or other diagram syntax
  • Downstream skills should never directly edit solution.blueprint.json
  • solution.handoff.json is viewer-only metadata, not a downstream narrative input

Sandbox Execution

When running in an isolated Python sandbox (Jupyter, notebook, cloud REPL) that auto-installs dependencies:

  1. The sandbox uses scripts directly. Run execution scripts from the repository root:
   import subprocess
   subprocess.run(["python", "scripts/business_blueprint/cli.py", "--export", "solution.blueprint.json"])

- sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) — will raise NameError - subprocess.run(["business-blueprint", ...]) — sandbox runs Python cells, not shell - os.system() — same reason

Architecture Diagram Generation

When user requests an architecture diagram (keywords: "架构图", "architecture diagram", "--export", "diagram"):

  1. Read references/architecture-design-system.md for the complete design system.
  2. Read the appropriate template from references/architecture-templates/ based on the user's domain:

- AWS/Serverless/Lambda → serverless.md - Microservices/Kubernetes/微服务 → microservices.md - Other → use serverless.md as a structural reference

  1. Read the blueprint JSON to extract entities and flow steps.
  2. Generate a self-contained HTML file with inline SVG following the design system rules.
  3. Write the output file to the same directory as the blueprint JSON.

If the request does not match one of the supported standard templates above, stay on the default freeflow export path. Do not switch to another generic view type as a fallback. If a standard template would create a squeezed, clipped, or overcrowded diagram, stop using the fixed template geometry and fall back to freeflow or a wrapped multi-row layout.

Route eligibility matrix

Use an explicit route contract before rendering:

RouteStructural prerequisitesFirst fallbackTerminal behavior
freeflowAny valid blueprint with at least one renderable node or relationNoneIf integrity still fails, export exits non-zero with a structural diagnostics payload
architecture-templateRecognizable L→R architecture shape, categorized systems, limited per-layer density, and no route-breaking overflow riskfreeflowSame as above
posterClear layer/group structure with bounded peer density per row or wrapped-row supportwrapped poster or freeflowSame as above
swimlaneActor-owned flow steps with meaningful lane groupingfreeflowSame as above
hierarchyStable tree/group relationship with low ambiguity in parent-child groupingfreeflowSame as above
evolutionOrdered chronological or staged progression datafreeflowSame as above

Do not invent route heuristics ad hoc inside a renderer. Route eligibility must stay explicit and reviewable.

Generation Rules

  • Use dark mode by default (#020617 bg + 40px grid). Only use light mode when the user explicitly asks for it.
  • L→R data flow: Clients(左) → Frontend → Backend → Database(右)
  • Map systems[].category to semantic colors from the design system
  • Map systems[].properties.type == "aws" → AWS Region boundary box
  • Map systems[].properties.type == "k8s" → Kubernetes Cluster boundary box
  • Use flowSteps[].seqIndex for L→R ordering
  • Component sizing: 0-1 cap = small(44px h), 2-4 = medium(80px h), 5+ = large(80px h)
  • Layout must be content-driven. Never force every node in a layer into one fixed row if that creates toothpaste-style squeezing.
  • When a layer has more than 3 peer nodes, or labels/features become tight, wrap into multiple rows or widen the canvas before shrinking the content.
  • Render users/actors as actor labels, badges, or lane headers by default. Do not render them as ordinary system cards unless the user explicitly asks for that visual treatment.
  • Legend must live in a bottom safe area and participate in canvas sizing. Never place the legend as a floating overlay in the top-right corner.
  • Final SVG/HTML height must be derived from the bottom-most node, legend, summary cards, and footer plus padding. Do not use fixed-height wrappers or overflow: hidden that can clip the last row.
  • Z-order: bg → grid → title → region → arrows → nodes → legend → cards → footer
  • Component border: rx="8", stroke-width="2"
  • Region border: rx="16", stroke-dasharray="8,4", opacity="0.4"
  • Geometry-sensitive integrity checks must use the numeric thresholds from evals/export-integrity-thresholds.json, not prose heuristics.

Output

  • Single HTML file: {blueprint_stem}.html alongside the blueprint JSON
  • No external dependencies (except Google Fonts CDN for JetBrains Mono)
  • Opens in any browser, printable to PDF

Error Handling

  • If --validate returns errors: fix structural issues before proceeding to --export.
  • If --validate returns only warnings: proceed but note the warnings in any handoff.
  • If Python version < 3.12: the package will refuse to install. Use python3 -m business_blueprint.cli with system Python as fallback.
  • If a specialized route fails integrity: fall back to its configured fallback route.
  • If freeflow also fails integrity: export exits non-zero with a structural diagnostics payload instead of emitting a silently broken artifact.

Cross-Platform Scope

Phase 2 does not attempt full Windows terminal parity.

Known deferred cases:

  • PowerShell pipe quirks beyond documented CLI contract tests
  • console-default encoding issues outside explicit UTF-8 execution paths

Accepted workaround for encoding-sensitive runs:

Use scripts directly (pure Skill, no package structure)

subprocess.run(["python", "scripts/business_blueprint/cli.py", "--export", str(blueprint_path)])

  • set PYTHONIOENCODING=utf-8 where needed

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

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。

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