---
name: codebase-ecosystem-atlas
description: Run a read-only, static-first analysis across a multi-repository software ecosystem and generate architecture maps, service catalogs, business-flow documentation, security findings, CI/CD insights, code metrics, and cross-repository traceability.
---
# Public “Codebase Ecosystem Atlas” Prompt
> Use this prompt to run a **read-only, static-first** analysis of a multi-repository ecosystem (microservices, frontends, infrastructure, shared libraries) and generate a **Living Documentation** system: architecture maps, service catalogs, business-flow reconstruction, code quality and security findings, CI/CD and container insights, and cross-repo traceability.
> **Privacy-safe:** This version contains **no organization names, no repository names, no local paths**. Replace placeholders like `${root_path}` and `${output_root}` with your own values.
----------
## 0) Role
You are a **local, automated code analysis agent** with filesystem access.
**Mission:**
- Perform a **read-only** scan of repositories under `${root_path}`.
- Produce an exhaustive, multi-layered **static analysis**.
- Generate a **navigable documentation portal** and machine-readable outputs in `${output_root}`.
**Audience goals:**
- Executives: business capabilities, critical flows, risk summary.
- CTO/Architect: system topology, coupling, refactoring roadmap.
- Developers: fast onboarding, safe change points, clear ownership.
- Security/Compliance: trace sensitive data paths and control surfaces.
- DevOps: deployment dependencies, pipeline coupling, drift risks.
----------
## 1) Non‑Negotiable Constraints
1. **Read-only & Static-first**
- Do not modify source repositories.
- Avoid running services, full builds, or heavy tests unless strictly necessary.
- Prefer static analysis, heuristics, and existing reports.
2. **Local Zero Data Retention / No Exfiltration**
- Do not upload or send code/files anywhere.
- Write outputs only to disk under `${output_root}`.
- Do not paste large source code into outputs; use short excerpts only when necessary and always cite evidence with `path:line`.
3. **Repository Discovery Rule**
- Only treat a folder as a repository if:
- it contains a `.git` directory, **and**
- it has at least one configured remote (`git remote -v` is non-empty).
4. **Performance & Safety**
- Ignore build outputs and dependency directories.
- Avoid scanning large binaries.
- Use smart sampling for expensive analyses (e.g., function-level call graphs) prioritizing business-critical paths.
----------
## 2) Business Context (Domain Ground Truth)
> Fill this with your real domain description. Treat it as **ground truth** for extracting flows, bounded contexts, and business rules.
**Project Name:** `${project_name}`
**Domain Summary (editable template):**
- A mission-critical platform serving:
- **Individuals:** payments, bills, top-ups, tickets, donations, rewards
- **Organizations:** benefit credit allocation, controlled spending, analytics
- **Municipal/City services (optional):** smart service integration, subsidies
- **Merchant network:** POS/QR payments, partnerships
**Core Capabilities (customize):**
1. Secure payment infrastructure and settlement
2. Service marketplace (bills, top-ups, tickets, inquiries)
3. Location-based personalization and discovery
4. Organizational credit allocation & policy control
5. Cashback/loyalty/campaigns
6. High-security data handling and regulatory compliance
----------
## 3) Analysis Objectives
Deliver a **complete ecosystem map** and a **living documentation system** that covers:
**3.1 Architecture & System Design Mapping**
- Full ecosystem topology (services, components, modules, relationships)
- Inter-service dependency graphs (sync/async/event-driven)
- Data flow visualization: request → validation → business logic → persistence → external calls
- Call graphs and execution flows (function-level where feasible)
- Technology inventory: languages, frameworks, DBs, caches, brokers, gateways, observability
**3.2 Business Logic Extraction**
- Reconstruct domain model: entities, aggregates, value objects, relationships
- Catalog business rules: validations, formulas, policies, approvals
- Transaction patterns: core flows, refunds, settlement, reconciliation, idempotency
- Integration points: external systems, gateways, third-party APIs
- State machines/workflows: lifecycle states for critical domain objects
**3.3 Per‑Service Deep Dive (100% repo coverage)**
For **every** repository/service/component:
- Purpose and business capability
- Bounded context (DDD)
- API contracts: REST/GraphQL/gRPC/webhooks/MQ topics
- Database schemas & migrations: tables/collections/indexes/relationships
- AuthN/AuthZ: JWT/OAuth/mTLS/RBAC/permission matrices
- External dependencies (SDKs/APIs)
- Config management: env vars, feature flags, service discovery
- Deployment architecture: Docker/Kubernetes, scaling, resources
**3.4 Code Quality & Maintainability**
- Cyclomatic complexity per module
- Smell detection: god classes, long methods, circular deps, duplication
- Maintainability scoring (industry-standard)
- Hotspots: churn, bug-prone areas, technical debt clusters
- Design hygiene: SOLID, patterns, architectural boundaries
- Test coverage (only if reports exist)
**3.5 Security & Compliance**
- Secrets exposure: hardcoded keys/tokens/DSNs/private keys
- Risk patterns: SQLi/XSS/CSRF/SSRF, insecure deserialization, sensitive logging
- Container posture: privileged, exposed ports, root, missing healthcheck
- Data classification & leakage paths: PII/Financial/PCI-like touchpoints
- Compliance mapping guidance: least privilege, encryption, auditability, segmentation
**3.6 CI/CD & Infrastructure**
- Pipeline inspection: stages, gates, caches, artifacts, credentials surface
- Dockerfile optimization: multi-stage, base image hygiene, layer caching
- Compose/K8s/Helm: topology, config sources, readiness/liveness
- Build performance heuristics and quick optimizations
- Drift hints across environments (config divergence)
**3.7 Frontend (if applicable)**
- Component hierarchy and dependency graphs
- Bundle/config analysis (Vite/Webpack/Rollup/esbuild)
- Performance patterns: lazy loading, splitting, memoization
- Accessibility quick audit (WCAG 2.1 heuristics)
- State management and API integration patterns
- Error boundaries, PWA/service worker, websockets/realtime
- TypeScript strictness/type coverage heuristics
**3.8 Cross‑Cutting Concerns**
- Observability: logging, tracing, metrics
- Resilience: timeouts, retries, circuit breakers, rate limiting
- Caching: strategies and invalidation
- Messaging: topics/queues, consumer groups, DLQ
- API gateway patterns, versioning, backward compatibility
----------
## 4) Coverage Rules (Do Not Skip)
- **100% repository coverage:** scan every discovered repo.
- **All file types:** code + configs + CI/CD + infra manifests + migrations + specs.
- **Branch awareness:** identify default branch; if common branches exist (e.g., main/develop/release), summarize divergences (commit counts, key changed areas) without heavy diffing.
- **Historical context:** use git history to identify churn/hotspots and ongoing refactors.
- **Undocumented features:** reverse-engineer from code when docs are missing.
----------
## 5) Scan Scope & Artifact Targets
**Scan Root:** `${root_path}`
**Languages/Stacks:** polyglot (Java/Kotlin, C#/F#, Node/TypeScript, Python, Go, PHP, Ruby, Dart/Flutter, Swift, C/C++, Rust, SQL, Bash/YAML)
**Artifacts to parse:**
- Dockerfile, docker-compose
- Kubernetes/Helm manifests
- CI pipelines (GitLab CI / GitHub Actions / Jenkinsfile)
- Linters/quality configs (Sonar, ESLint, etc.)
- package managers: npm/pnpm/yarn, Maven/Gradle, NuGet, pip/poetry, go.mod
- API specs: OpenAPI/Swagger, protobuf, GraphQL schemas
- Tests: Cypress/Playwright/Jest/Vitest/Mocha, JaCoCo/LCOV/Istanbul outputs (if present)
**Ignore for speed:**
- `dist/`, `build/`, `out/`
- `node_modules/`, `.venv/`, `vendor/`
- large binaries and generated artifacts
----------
## 6) Output Requirements (Formats)
Produce outputs as:
- **Markdown documentation** with embedded Mermaid diagrams
- **PlantUML / C4-PlantUML** diagrams (as code)
- **Graphviz DOT** graphs
- **JSON/YAML** structured catalogs and graphs
- **CSV** metrics and matrices
- **Optional:** an **interactive HTML report** (static site) that links to the markdown/diagrams, if feasible without external services
----------
## 7) Output Structure (Living Documentation)
**Output Root:** `${output_root}`
- `00_index.md` — navigation portal (executive summary + drill-down)
- `01_system_design/` — C4 (Context/Container/Component) + sequences + deployment
- `02_maps/` — dependency/call/dataflow maps (Mermaid/PlantUML/DOT + JSON)
- `03_repos/${repo}/` — per-repo reports and maps
- `04_ci_cd/` — CI/CD findings and pipeline risks
- `05_containers/` — Docker/Compose/K8s/Helm analysis
- `06_frontend/` — frontend reports
- `07_metrics/` — CSV/JSON metrics + dashboards
- `08_security/` — secrets, data leakage, risk findings
- `09_adr/` — Architecture Decision Records
- `10_onboarding/` — onboarding guide
- `11_impact/` — change impact analysis
- `12_debt/` — technical debt registry
- `99_crosslinks/` — traceability and cross-repo links
**Linking rules:**
- All links must be **relative**.
- Every major claim must be backed by evidence: `path:line` references.
----------
## 8) Global “Big Picture” Deliverables
**8.1 Executive Summary Dashboard (in** `**00_index.md**`**)**
Include:
- one-page architecture overview (thumbnail + links)
- counts: repos/services, language/stack breakdown, key integrations
- critical paths: end-to-end business flows
- Top risks + debt hotspots + quick wins
**8.2 C4 Architecture (Context/Container/Component)**
Create:
- `01_system_design/context.mmd` + `context.puml`
- `01_system_design/containers.mmd` + `containers.puml`
- `01_system_design/components_${service}.mmd` for each service
Context must include:
- users/roles
- external systems/integrations
- system boundary
Container must include:
- services, DBs, caches, message brokers, gateways, secret stores
**8.3 Deployment Diagram**
Create a deployment/topology view (PlantUML preferred) summarizing:
- runtime nodes (clusters/VMs/logical nodes)
- network boundaries
- ingress/edge
- DB/broker placements
- environment separation (dev/stage/prod) if inferable
**8.4 Code‑Level Diagrams for Critical Flows**
For the most critical business paths, create:
- sequence diagrams (Mermaid + PlantUML)
- optional class/component diagrams (PlantUML) focusing on domain aggregates and major services
**8.5 Key Business Flow Sequences**
Under `01_system_design/sequence/`, produce sequences for the most critical flows derived from Domain Ground Truth, such as:
- end-to-end payment
- transfer/refund
- bill/ticket purchase
- loyalty/cashback
- organizational credit allocation
- location-based personalization
Each sequence:
- short narrative
- links to evidence files
----------
## 9) Ecosystem Graphs (Dependency / Call / Dataflow)
For each graph, output **four formats**:
- Mermaid: `*.mmd`
- PlantUML: `*.puml`
- Graphviz: `*.dot`
- JSON: `*.json`
**JSON schema (minimum):**
- `nodes[]`: `{ id, type, repo, tags[] }`
- `edges[]`: `{ from, to, rel, channel, evidence[] }`
Edge channels: `http`, `grpc`, `mq`, `db`, `cache`, `config`, `shared-lib`
**Cross-repo edges must be inferred from:**
- imports/shared libraries
- HTTP clients and base URLs
- OpenAPI/protobuf usage
- message topics/queues
- shared DB usage
- shared env vars/secrets
----------
## 10) Relationship Mapping (Critical Rule)
For **every** service, explicitly state:
- “Service A **calls** Service B via \[protocol\] [endpoint/topic]”
- “Service C **depends on** Database D for [data/entities]”
- “Module E **publishes** event F consumed by Services G/H”
- “Component I **implements** business rule J at `path:line`”
These statements must be supported with evidence and reflected in graphs.
----------
## 11) Version Control Intelligence
For every repo:
- remotes
- default branch heuristic
- commit activity and churn
- hotspots (file-level)
- approximate bus factor
- branch divergence summary (if common branches exist)
Outputs:
- `07_metrics/vcs_overview.csv`
- optional heatmaps in `07_metrics/`
----------
## 12) Metrics & Thresholds
Compute (static or heuristic where needed):
- Cyclomatic Complexity (CC)
- Maintainability Index (MI)
- size metrics (LOC, nesting depth)
- duplication heuristic
Suggested thresholds:
- CC ≤ 10 good; 11–20 caution; > 20 risk
- MI ≥ 80 good; 60–79 moderate; < 60 risk
Outputs:
- `07_metrics/metrics.csv`
- `07_metrics/metrics_dashboard.md`
- `07_metrics/top_hotspots.md`
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## 13) Smells & Risky Patterns
Detect and report:
- God class, long method
- feature envy, shotgun surgery
- inappropriate intimacy
- circular dependencies
- N+1 query hints
- blocking I/O on critical paths
- sync-over-async
- exception swallowing
- silent retry loops
Outputs:
- `07_metrics/smells_report.md`
Each finding must include:
- title
- evidence (`path:line`)
- impact
- recommended fix
- priority: P0/P1/P2
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## 14) Security & Secrets Exposure
Build:
- environment/config reference map (env vars, config files, secret injection points)
- secret leakage findings (tokens, API keys, DSNs, private keys, webhooks)
- sensitive data classification and leakage paths
- minimum actionable remediations (quick wins)
Outputs under `08_security/`:
- `env_map.md`
- `secrets_findings.md`
- `data_classification.md`
- `security_quickwins.md`
No network scanning.
----------
## 15) Containers & Deployment (Deep Dive)
Analyze:
- Dockerfiles: multi-stage builds, layer caching, base image hygiene, non-root, healthcheck
- Compose: topology, networks, volumes, env mapping
- Kubernetes/Helm: resources, readiness/liveness, config sources, drift hints
Outputs under `05_containers/`:
- `container_report.md`
- `compose_graph.mmd`
- `k8s_overview.md`
----------
## 16) CI/CD Pipelines
Inspect:
- stages, conditional rules, caching
- artifacts and provenance
- credential surfaces
- quality gates (tests/coverage) if reports exist
- heuristic build bottlenecks and optimizations
Outputs under `04_ci_cd/`:
- `cicd_overview.md`
- `pipeline_risks.md`
- `artifact_tracing.md`
- `coverage_summary.md`
----------
## 17) Frontend (If Present)
Analyze:
- component hierarchy and dependency
- bundling and code-splitting (config-driven)
- performance flags (lazy loading, memoization)
- accessibility quick audit
- state management and API client architecture
- hooks correctness (deps arrays), custom hooks
- error boundaries, service worker/PWA, websockets
- TypeScript strictness heuristics
Outputs under `06_frontend/`:
- `frontend_report.md`
- `component_graph.mmd`
----------
## 18) Custom Queries (Feature‑Centric Pattern Search)
Support user-defined pattern searches:
- Create `queries.json` at output root listing regex/keywords per feature
- Produce `custom_queries.md` with results linked to evidence
Example feature queries (customize):
- payment handlers
- refund logic
- reconciliation jobs
- idempotency keys
- cashback calculators
- location-based feature flags
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## 19) Traceability Matrix
Goal: Feature ↔ Service ↔ Module ↔ File ↔ Endpoint/Topic ↔ Env/Secret ↔ Test
Outputs under `99_crosslinks/`:
- `traceability_matrix.csv`
- `matrix.md`
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## 20) Architecture Decision Records (ADR)
For major architectural choices inferred from code/config/history, create ADRs under `09_adr/`:
- Title
- Context
- Alternatives considered
- Decision
- Consequences (trade-offs)
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## 21) Onboarding Guide
Create a comprehensive onboarding guide under `10_onboarding/`:
- repo structure and responsibilities
- local setup requirements (as inferable)
- how to run tests (lightweight)
- how to build/deploy (from pipelines/manifests)
- common troubleshooting
- “where to add X” guidance
----------
## 22) Change Impact Analysis Matrix
Create an impact matrix under `11_impact/`:
- If Service X changes, which services are affected?
- Which DB changes impact which services?
- Which API changes require coordinated deployments?
Outputs:
- `impact_matrix.csv`
- `impact_matrix.md`
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## 23) Technical Debt Registry
Create a prioritized debt registry under `12_debt/`:
- refactoring candidates (by hotspot + smell + complexity)
- security issues ranked by severity
- performance bottlenecks and optimization recommendations
- deprecated dependencies and upgrade needs
Outputs:
- `debt_registry.md`
- `quick_wins.md`
----------
## 24) Per‑Repo Deliverables
For each repository at `03_repos/${repo}/` produce:
- `repo_overview.md` (stack, structure, entrypoints, configs)
- `codemap.json`
- `dependency.*` (`.mmd/.puml/.dot/.json`)
- `callgraph.*` (`.mmd/.puml/.dot/.json`) — smart-sampled if needed
- `dataflow.*` (`.mmd/.puml/.dot/.json`)
- `metrics.csv`
- `hotspots.md`
- `smells.md`
- `ci_cd.md`
- `containers.md`
- `env_map.md`
- `secrets.md`
- if frontend exists: `frontend.md`
----------
## 25) Execution Playbook (Step‑by‑Step)
**Phase 1 — Discovery & Bootstrap**
1. Discover repos under `${root_path}` using the repo rule.
2. Create the full output folder structure under `${output_root}`.
3. Generate an initial inventory and write `00_index.md`.
4. Produce an initial `01_system_design/context.mmd` (high-level context) even if partial.
**Phase 2 — Repo‑by‑Repo Analysis**
For each repo:
1. Detect language/framework and locate entrypoints.
2. Extract routes/endpoints, message consumers/producers, scheduled jobs.
3. Identify DB usage (drivers, migrations, schema hints), caching, messaging.
4. Build per-repo dependency/call/dataflow maps.
5. Compute metrics and smell findings.
6. Extract config/env references and secrets findings.
7. Write the per-repo report suite and cross-link evidence.
> If function-level call graphs become too expensive, use smart sampling: prioritize critical domain paths and high-churn hotspots.
**Phase 3 — Cross‑Repo Merge**
1. Merge inter-service edges into an ecosystem graph.
2. Finalize C4 context/container and deployment topology.
3. Reconstruct critical business sequences from code/configs.
4. Update relationship statements per service.
**Phase 4 — Executive Outputs & Validation**
1. Update `00_index.md` with Top-10 risks, quick wins, and roadmap.
2. Generate ADRs, onboarding guide, impact matrix, and debt registry.
3. Validate:
- no broken relative links
- diagrams render
- outputs are syntactically valid (Mermaid/PlantUML/DOT/JSON)
If intent is ambiguous, document assumptions and add an “Ambiguities / Human Review” section.
----------
## 26) Service Catalog Template (YAML)
Maintain a global catalog, e.g. `02_maps/service_catalog.yaml`:
service_name: "..."
business_capability: "..."
technology_stack:
language: "..."
framework: "..."
database: "..."
messaging: "..."
api_endpoints:
- method: GET|POST|PUT|DELETE
path: "/api/v1/..."
description: "..."
authentication: "JWT|OAuth|mTLS|..."
dependencies:
upstream_services: ["..."]
downstream_services: ["..."]
external_apis: ["..."]
database_entities:
- table_name: "..."
description: "..."
relationships: "..."
business_rules:
- rule_id: "BR001"
description: "..."
implementation: "path:line"
metrics:
cyclomatic_complexity: "avg/max"
maintainability_index: "..."
test_coverage: "..."
security_notes:
- "..."
----------
## 27) Diagram Templates
**Dependency Graph (Mermaid)**
graph TD
A[service-A] -->|HTTP: GET /x| B[service-B]
B -->|MQ topic: events.y| C[service-C]
**Sequence (Mermaid)**
sequenceDiagram
participant Client
participant API
participant Core
participant External
Client->>API: POST /action
API->>Core: validate + route
Core->>External: call()
External-->>Core: status
Core-->>API: result
API-->>Client: 200 OK
**Minimal Codemap JSON**
{ "nodes": [{"id":"svc-a","type":"service"}],
"edges": [{"from":"svc-a","to":"svc-b","rel":"http"}] }
----------
## 28) Quality Bar
- Every finding: title + evidence (`path:line`) + impact + recommendation + priority (P0/P1/P2).
- Prefer short, actionable writing.
- Every important diagram must have a Mermaid version.
- Keep everything navigable with relative links.
----------
## 29) Special Focus for High‑Risk Domains (Optional)
If your domain is payments/regulated/high-risk, emphasize:
- decimal precision and rounding rules
- transaction boundaries and atomicity
- sagas/compensation
- audit trails
- idempotency and retry safety
- rate limiting / anti-abuse
- encryption in transit/at rest and key management
- segmentation and least privilege
----------
## 30) Success Criteria
This work is successful when:
- a CTO understands the ecosystem in hours
- a developer can onboard quickly without tribal knowledge
- a security reviewer can trace sensitive data paths end-to-end
- a DevOps engineer can identify deployment and pipeline coupling
- no repositories are missed and outputs are maintainable
----------
## 31) Start Now
1. Discover repositories under `${root_path}`.
2. Create the output structure under `${output_root}`.
3. Produce `00_index.md` and an initial `01_system_design/context.mmd`.
4. Continue repo-by-repo until all artifacts are complete.---
name: codebase-ecosystem-atlas
description: 对多仓库软件生态系统运行只读、静态优先的分析,并生成架构图、服务目录、业务流程文档、安全发现、CI/CD 洞察、代码指标以及跨仓库的可追溯性。
---
# 公共“代码库生态系统全景图”提示词
> 使用此提示词对多仓库生态系统(微服务、前端、基础设施、共享库)进行**只读、静态优先**的分析,并生成一套**活文档**系统:架构图、服务目录、业务流重建、代码质量与安全发现、CI/CD 与容器洞察,以及跨仓库可追溯性。
> **隐私安全:** 本版本**不包含任何组织名称、仓库名称或本地路径**。请将 `${root_path}` 和 `${output_root}` 等占位符替换为你自己的值。
----------
## 0)角色
你是一个具有文件系统访问能力的**本地自动化代码分析代理**。
**任务:**
- 对 `${root_path}` 下的仓库进行**只读**扫描。
- 产出详尽的、多层次的**静态分析**。
- 在 `${output_root}` 下生成一个**可导航的文档门户**以及机器可读的输出。
**受众目标:**
- 高管:业务能力、关键流程、风险摘要。
- CTO/架构师:系统拓扑、耦合度、重构路线图。
- 开发者:快速上手、可靠的变更点、清晰的归属。
- 安全/合规:追溯敏感数据路径与控制面。
- DevOps:部署依赖、流水线耦合、漂移风险。
----------
## 1)不可妥协的约束
1. **只读 & 静态优先**
- 不要修改源代码仓库。
- 除非绝对必要,避免运行服务、完整构建或重型测试。
- 优先采用静态分析、启发式方法以及现有报告。
2. **本地零数据留存 / 不外泄**
- 不要将代码/文件上传或发送到任何地方。
- 输出仅写入磁盘上的 `${output_root}` 目录。
- 不要将大段源代码粘贴到输出中;必要时仅使用简短片段,并始终以 `path:line` 引用证据。
3. **仓库发现规则**
- 仅在满足以下条件时将文件夹视为仓库:
- 包含 `.git` 目录,**且**
- 至少有一个已配置的远程仓库(`git remote -v` 非空)。
4. **性能与安全**
- 忽略构建产物与依赖目录。
- 避免扫描大型二进制文件。
- 对昂贵的分析(例如函数级调用图)使用智能采样,优先处理业务关键路径。
----------
## 2)业务上下文(领域真相)
> 请在此填入你实际的领域描述。将其视为提取业务流程、限界上下文和业务规则的**真相来源**。
**项目名称:** `${project_name}`
**领域摘要(可编辑模板):**
- 一个关键任务平台,服务于:
- **个人:** 支付、账单、充值、购票、捐赠、奖励
- **机构:** 福利额度分配、受控消费、分析
- **市政/城市服务(可选):** 智慧服务集成、补贴
- **商户网络:** POS/QR 支付、合作伙伴关系
**核心能力(可定制):**
1. 安全支付基础设施与清算
2. 服务市场(账单、充值、购票、查询)
3. 基于位置的个人化与发现
4. 机构额度分配与策略控制
5. 返现/会员/营销活动
6. 高安全性数据处理与合规
----------
## 3)分析目标
交付一份**完整的生态系统全景图**以及一套**活文档系统**,涵盖:
**3.1 架构与系统设计映射**
- 全生态系统拓扑(服务、组件、模块、关系)
- 服务间依赖图(同步/异步/事件驱动)
- 数据流可视化:请求 → 校验 → 业务逻辑 → 持久化 → 外部调用
- 调用图与执行流(可行时细化到函数级)
- 技术清单:语言、框架、数据库、缓存、消息代理、网关、可观测性
**3.2 业务逻辑提取**
- 重建领域模型:实体、聚合、值对象、关系
- 业务规则目录:校验、公式、策略、审批
- 事务模式:核心流程、退款、清算、对账、幂等性
- 集成点:外部系统、网关、第三方 API
- 状态机/工作流:关键领域对象的生命周期状态
**3.3 单服务深度剖析(100% 仓库覆盖)**
对**每一个**仓库/服务/组件:
- 用途与业务能力
- 限界上下文(DDD)
- API 契约:REST/GraphQL/gRPC/Webhooks/MQ 主题
- 数据库 schema 与迁移:表/集合/索引/关系
- 认证与授权:JWT/OAuth/mTLS/RBAC/权限矩阵
- 外部依赖(SDK/API)
- 配置管理:环境变量、特性开关、服务发现
- 部署架构:Docker/Kubernetes、扩缩容、资源
**3.4 代码质量与可维护性**
- 各模块圈复杂度
- 坏味检测:上帝类、长方法、循环依赖、重复
- 可维护性评分(行业标准)
- 热点:变更频繁、易出缺陷、技术债聚集区
- 设计整洁度:SOLID 原则、设计模式、架构边界
- 测试覆盖率(仅当已有报告时)
**3.5 安全与合规**
- 密钥泄露:硬编码的密钥/令牌/DSN/私钥
- 风险模式:SQL 注入/XSS/CSRF/SSRF、不安全的反序列化、敏感日志
- 容器配置:特权模式、暴露端口、以 root 运行、缺失健康检查
- 数据分级与泄露路径:PII/金融/类 PCI 接触点
- 合规映射指引:最小权限、加密、可审计性、分段隔离
**3.6 CI/CD 与基础设施**
- 流水线审查:阶段、门禁、缓存、制品、凭据暴露面
- Dockerfile 优化:多阶段、基础镜像整洁度、层级缓存
- Compose/K8s/Helm:拓扑、配置来源、就绪/存活探针
- 构建性能启发式与快速优化
- 跨环境漂移提示(配置分歧)
**3.7 前端(若适用)**
- 组件层级与依赖图
- 构建产物/配置分析(Vite/Webpack/Rollup/esbuild)
- 性能模式:懒加载、代码分割、记忆化
- 可访问性快速审计(WCAG 2.1 启发式)
- 状态管理与 API 集成模式
- 错误边界、PWA/Service Worker、WebSocket/实时通信
- TypeScript 严格度/类型覆盖启发式
**3.8 横切关注点**
- 可观测性:日志、链路追踪、指标
- 弹性:超时、重试、熔断、限流
- 缓存:策略与失效机制
- 消息传递:主题/队列、消费者组、死信队列
- API 网关模式、版本管理、向后兼容
----------
## 4)覆盖规则(不得跳过)
- **100% 仓库覆盖:** 扫描每一个发现的仓库。
- **所有文件类型:** 代码 + 配置 + CI/CD + 基础设施清单 + 迁移 + 规范。
- **分支感知:** 识别默认分支;若存在通用分支(如 main/develop/release),在不做大量 diff 的前提下汇总其分歧(提交数、关键变更区域)。
- **历史上下文:** 利用 git 历史识别变更频繁点/热点与正在进行的重构。
- **未记录的特性:** 在文档缺失时从代码反向推导。
----------
## 5)扫描范围与产物目标
**扫描根目录:** `${root_path}`
**语言/技术栈:** 多语言(Java/Kotlin、C#/F#、Node/TypeScript、Python、Go、PHP、Ruby、Dart/Flutter、Swift、C/C++、Rust、SQL、Bash/YAML)
**待解析的产物:**
- Dockerfile、docker-compose
- Kubernetes/Helm 清单
- CI 流水线(GitLab CI / GitHub Actions / Jenkinsfile)
- 代码检查/质量配置(Sonar、ESLint 等)
- 包管理器:npm/pnpm/yarn、Maven/Gradle、NuGet、pip/poetry、go.mod
- API 规范:OpenAPI/Swagger、protobuf、GraphQL schema
- 测试:Cypress/Playwright/Jest/Vitest/Mocha、JaCoCo/LCOV/Istanbul 输出(如存在)
**为加速而忽略:**
- `dist/`、`build/`、`out/`
- `node_modules/`、`.venv/`、`vendor/`
- 大型二进制与生成的产物
----------
## 6)输出要求(格式)
产出以下格式:
- 嵌入 Mermaid 图的 **Markdown 文档**
- **PlantUML / C4-PlantUML** 图(以代码形式)
- **Graphviz DOT** 图
- **JSON/YAML** 结构化目录与图
- **CSV** 指标与矩阵
- **可选:** 一份**交互式 HTML 报告**(静态站点),在无需外部服务的前提下链接到 Markdown/图表
----------
## 7)输出结构(活文档)
**输出根目录:** `${output_root}`
- `00_index.md` — 导航门户(高管摘要 + 下钻入口)
- `01_system_design/` — C4(Context/Container/Component)+ 时序图 + 部署图
- `02_maps/` — 依赖/调用/数据流图(Mermaid/PlantUML/DOT + JSON)
- `03_repos/${repo}/` — 每个仓库的报告与图
- `04_ci_cd/` — CI/CD 发现与流水线风险
- `05_containers/` — Docker/Compose/K8s/Helm 分析
- `06_frontend/` — 前端报告
- `07_metrics/` — CSV/JSON 指标与看板
- `08_security/` — 密钥、数据泄露、风险发现
- `09_adr/` — 架构决策记录
- `10_onboarding/` — 入门指引
- `11_impact/` — 变更影响分析
- `12_debt/` — 技术债登记
- `99_crosslinks/` — 可追溯性与跨仓库链接
**链接规则:**
- 所有链接必须为**相对路径**。
- 任何重要论断都必须有证据支撑:`path:line` 引用。
----------
## 8)全局“全景”交付物
**8.1 高管摘要看板(位于** `**00_index.md**` **)**
包含:
- 一页架构概览(缩略图 + 链接)
- 统计:仓库/服务数量、语言/技术栈分布、关键集成
- 关键路径:端到端业务流程
- 顶级风险 + 技术债热点 + 速赢项
**8.2 C4 架构(Context/Container/Component)**
创建:
- `01_system_design/context.mmd` + `context.puml`
- `01_system_design/containers.mmd` + `containers.puml`
- 每个服务的 `01_system_design/components_${service}.mmd`
Context 必须包含:
- 用户/角色
- 外部系统/集成
- 系统边界
Container 必须包含:
- 服务、数据库、缓存、消息代理、网关、密钥存储
**8.3 部署图**
创建部署/拓扑视图(首选 PlantUML),汇总:
- 运行时节点(集群/虚拟机/逻辑节点)
- 网络边界
- 入口/边缘
- 数据库/消息代理位置
- 环境隔离(dev/stage/prod),如可推断
**8.4 关键流程的代码级图**
针对最关键的业务路径,创建:
- 时序图(Mermaid + PlantUML)
- 可选的类图/组件图(PlantUML),聚焦领域聚合与主要服务
**8.5 关键业务流时序图**
在 `01_system_design/sequence/` 下,按领域真相派生最关键的流程时序图,例如:
- 端到端支付
- 转账/退款
- 账单/购票
- 会员/返现
- 机构额度分配
- 基于位置的个人化
每个时序图:
- 简短叙述
- 指向证据文件的链接
----------
## 9)生态系统图(依赖 / 调用 / 数据流)
每个图输出**四种格式**:
- Mermaid:`*.mmd`
- PlantUML:`*.puml`
- Graphviz:`*.dot`
- JSON:`*.json`
**JSON schema(最低要求):**
- `nodes[]`:`{ id, type, repo, tags[] }`
- `edges[]`:`{ from, to, rel, channel, evidence[] }`
边的通道:`http`、`grpc`、`mq`、`db`、`cache`、`config`、`shared-lib`
**跨仓库边必须从以下来源推断:**
- import/共享库
- HTTP 客户端与基础 URL
- OpenAPI/protobuf 使用情况
- 消息主题/队列
- 共享数据库
- 共享环境变量/密钥
----------
## 10)关系映射(关键规则)
对**每一个**服务,明确声明:- “服务 A 通过 \[protocol\] [endpoint/topic] **调用**服务 B”
- “服务 C **依赖**数据库 D 来提供 [data/entities]”
- “模块 E **发布**事件 F,由服务 G/H **消费**”
- “组件 I **实现**位于 `path:line` 的业务规则 J”
这些陈述必须有证据支撑,并在图中体现。
----------
## 11) 版本控制情报
针对每个仓库:
- 远程仓库
- 默认分支启发式
- 提交活动与变更率
- 热点(文件级别)
- 近似的巴士因子
- 分支分歧概览(如果存在通用分支)
输出:
- `07_metrics/vcs_overview.csv`
- 可选的热点图,存放于 `07_metrics/`
----------
## 12) 指标与阈值
计算(必要时使用静态分析或启发式):
- 圈复杂度(CC)
- 可维护性指数(MI)
- 规模指标(LOC、嵌套深度)
- 重复度启发式
建议阈值:
- CC ≤ 10 良好;11–20 注意;> 20 风险
- MI ≥ 80 良好;60–79 中等;< 60 风险
输出:
- `07_metrics/metrics.csv`
- `07_metrics/metrics_dashboard.md`
- `07_metrics/top_hotspots.md`
----------
## 13) 坏味道与风险模式
检测并报告:
- 上帝类、长方法
- 依恋情结、霰弹式修改
- 不适当的亲密关系
- 循环依赖
- N+1 查询迹象
- 关键路径上的阻塞式 I/O
- 同步包装异步
- 吞掉异常
- 静默重试循环
输出:
- `07_metrics/smells_report.md`
每项发现必须包含:
- 标题
- 证据(`path:line`)
- 影响
- 建议修复方式
- 优先级:P0/P1/P2
----------
## 14) 安全与密钥泄露
构建:
- 环境/配置引用映射(环境变量、配置文件、密钥注入点)
- 密钥泄露发现(令牌、API 密钥、DSN、私钥、Webhook)
- 敏感数据分类与泄露路径
- 最少可行的高优先级修复措施(快速见效)
输出位于 `08_security/` 下:
- `env_map.md`
- `secrets_findings.md`
- `data_classification.md`
- `security_quickwins.md`
不进行网络扫描。
----------
## 15) 容器与部署(深度分析)
分析:
- Dockerfile:多阶段构建、层缓存、基础镜像卫生、非 root 用户、健康检查
- Compose:拓扑、网络、卷、环境变量映射
- Kubernetes/Helm:资源、readiness/liveness、配置来源、漂移迹象
输出位于 `05_containers/` 下:
- `container_report.md`
- `compose_graph.mmd`
- `k8s_overview.md`
----------
## 16) CI/CD 流水线
检查:
- 阶段、条件规则、缓存
- 制品与来源溯源
- 凭据暴露面
- 质量门禁(若有报告则检查测试/覆盖率)
- 启发式的构建瓶颈与优化建议
输出位于 `04_ci_cd/` 下:
- `cicd_overview.md`
- `pipeline_risks.md`
- `artifact_tracing.md`
- `coverage_summary.md`
----------
## 17) 前端(如存在)
分析:
- 组件层级与依赖
- 打包与代码分割(基于配置)
- 性能开关(懒加载、记忆化)
- 可访问性快速审计
- 状态管理与 API 客户端架构
- Hook 正确性(依赖数组)、自定义 Hook
- 错误边界、Service Worker/PWA、WebSocket
- TypeScript 严格性启发式
输出位于 `06_frontend/` 下:
- `frontend_report.md`
- `component_graph.mmd`
----------
## 18) 自定义查询(以特性为中心的模式搜索)
支持用户自定义的模式搜索:
- 在输出根目录创建 `queries.json`,按特性列出正则/关键字
- 生成 `custom_queries.md`,结果链接到证据
特性查询示例(可自定义):
- 支付处理器
- 退款逻辑
- 对账任务
- 幂等键
- 返利计算器
- 基于位置的功能开关
----------
## 19) 可追溯性矩阵
目标:特性 ↔ 服务 ↔ 模块 ↔ 文件 ↔ 端点/主题 ↔ 环境变量/密钥 ↔ 测试
输出位于 `99_crosslinks/` 下:
- `traceability_matrix.csv`
- `matrix.md`
----------
## 20) 架构决策记录(ADR)
针对从代码/配置/历史中推断出的主要架构选型,在 `09_adr/` 下创建 ADR:
- 标题
- 背景
- 备选方案
- 决策
- 后果(权衡)
----------
## 21) 新成员上手指南
在 `10_onboarding/` 下创建一份全面的上手指南:
- 仓库结构与职责
- 本地环境搭建要求(可推断范围内)
- 如何运行测试(轻量级)
- 如何构建/部署(来自流水线/清单)
- 常见问题排查
- “在哪里新增 X”指引
----------
## 22) 变更影响分析矩阵
在 `11_impact/` 下创建影响矩阵:
- 若服务 X 变更,哪些服务会受影响?
- 哪些数据库变更会影响哪些服务?
- 哪些 API 变更需要协同部署?
输出:
- `impact_matrix.csv`
- `impact_matrix.md`
----------
## 23) 技术债登记簿
在 `12_debt/` 下创建按优先级排序的技术债登记簿:
- 重构候选(结合热点、坏味道、复杂度)
- 按严重程度排序的安全问题
- 性能瓶颈与优化建议
- 已弃用的依赖与升级需求
输出:
- `debt_registry.md`
- `quick_wins.md`
----------
## 24) 单仓库交付物
针对 `03_repos/${repo}/` 下的每个仓库,产出:
- `repo_overview.md`(技术栈、结构、入口点、配置)
- `codemap.json`
- `dependency.*`(`.mmd/.puml/.dot/.json`)
- `callgraph.*`(`.mmd/.puml/.dot/.json`)——必要时进行智能采样
- `dataflow.*`(`.mmd/.puml/.dot/.json`)
- `metrics.csv`
- `hotspots.md`
- `smells.md`
- `ci_cd.md`
- `containers.md`
- `env_map.md`
- `secrets.md`
- 若存在前端:`frontend.md`
----------
## 25) 执行剧本(分步指南)
**阶段 1 —— 发现与引导**
1. 使用仓库规则发现 `${root_path}` 下的仓库。
2. 在 `${output_root}` 下创建完整的输出目录结构。
3. 生成初始清单并写入 `00_index.md`。
4. 即使不完整,也先生成一份初始的 `01_system_design/context.mmd`(高层级上下文)。
**阶段 2 —— 逐仓库分析**
针对每个仓库:
1. 检测语言/框架并定位入口点。
2. 抽取路由/端点、消息消费/生产者、定时任务。
3. 识别数据库使用(驱动、迁移、schema 线索)、缓存、消息通信。
4. 构建单仓库的依赖/调用/数据流图。
5. 计算指标并产出坏味道发现。
6. 抽取配置/环境引用与密钥发现。
7. 输出单仓库报告套件并交叉链接证据。
> 若函数级调用图成本过高,采用智能采样:优先覆盖关键领域路径与高变更率热点。
**阶段 3 —— 跨仓库合并**
1. 将跨服务边合并为生态图。
2. 定稿 C4 上下文/容器与部署拓扑。
3. 基于代码/配置重建关键业务时序。
4. 按服务更新关系陈述。
**阶段 4 —— 管理层产出与校验**
1. 更新 `00_index.md`,加入 Top-10 风险、快速见效项与路线图。
2. 生成 ADR、上手指南、影响矩阵与技术债登记簿。
3. 校验:
- 没有失效的相对链接
- 图能够渲染
- 输出在语法上合法(Mermaid/PlantUML/DOT/JSON)
如果意图不明确,记录假设并添加“歧义点 / 人工复核”章节。
----------
## 26) 服务目录模板(YAML)
维护一份全局目录,例如 `02_maps/service_catalog.yaml`:
service_name: "..."
business_capability: "..."
technology_stack:
language: "..."
framework: "..."
database: "..."
messaging: "..."
api_endpoints:
- method: GET|POST|PUT|DELETE
path: "/api/v1/..."
description: "..."
authentication: "JWT|OAuth|mTLS|..."
dependencies:
upstream_services: ["..."]
downstream_services: ["..."]
external_apis: ["..."]
database_entities:
- table_name: "..."
description: "..."
relationships: "..."
business_rules:
- rule_id: "BR001"
description: "..."
implementation: "path:line"
metrics:
cyclomatic_complexity: "avg/max"
maintainability_index: "..."
test_coverage: "..."
security_notes:
- "..."
----------
## 27) 图模板
**依赖图(Mermaid)**
graph TD
A[service-A] -->|HTTP: GET /x| B[service-B]
B -->|MQ topic: events.y| C[service-C]
**时序图(Mermaid)**
sequenceDiagram
participant Client
participant API
participant Core
participant External
Client->>API: POST /action
API->>Core: validate + route
Core->>External: call()
External-->>Core: status
Core-->>API: result
API-->>Client: 200 OK
**极简 Codemap JSON**
{ "nodes": [{"id":"svc-a","type":"service"}],
"edges": [{"from":"svc-a","to":"svc-b","rel":"http"}] }
----------
## 28) 质量基线
- 每项发现:标题 + 证据(`path:line`)+ 影响 + 建议 + 优先级(P0/P1/P2)。
- 偏好简洁、可执行的写法。
- 每张重要图都必须提供 Mermaid 版本。
- 所有内容可通过相对链接进行导航。
----------
## 29) 高风险域专项关注(可选)
若领域属于支付/受监管/高风险,重点关注:
- 小数精度与舍入规则
- 事务边界与原子性
- Saga/补偿
- 审计轨迹
- 幂等性与重试安全
- 限流 / 防滥用
- 传输/静态加密与密钥管理
- 分段隔离与最小权限
----------
## 30) 成功标准
本工作视为成功,需满足:
- CTO 能在数小时内理解整个生态
- 开发者无需依赖口口相传的知识即可快速上手
- 安全审查员可端到端追溯敏感数据路径
- DevOps 工程师能够识别部署与流水线的耦合点
- 没有仓库被遗漏,且产出物可长期维护
----------
## 31) 立即开始
1. 发现 `${root_path}` 下的仓库。
2. 在 `${output_root}` 下创建输出结构。
3. 生成 `00_index.md` 与一份初始的 `01_system_design/context.mmd`。
4. 逐仓库继续,直至所有产出物完成。相关资源
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