一个代码库架构分析 skill:追依赖、看影响、找死代码,但有门槛
装好之后怎么用
什么时候会用上它:Use Ontoly's deterministic Software Graph and MCP capabilities for architecture review, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source-file search.
怎么用:在 AI 工具里直接描述任务即可自动触发。显式调用的写法各端不同:Claude Code / Cursor 等用 /ontoly-software-graph,Codex 用 $ontoly-software-graph,Kimi Code 用 /skill:ontoly-software-graph,ZCODE 用 $ontoly-software-graph,Gemini CLI 以自动激活为主。
一个代码库架构分析 skill。
它能让 AI 基于 Ontoly 图来理解代码,而不是直接去翻源码。能做的事:
- 解释一个仓库的架构
- 追踪请求、路由、控制器、服务的依赖路径
- 找服务、模块、路由、配置的归属
- 重构前评估影响范围
- 审计死代码、循环依赖、未解析导入
- 基于图证据准备文档或架构评审
它的规则很硬:回答必须引用图证据(node ID、edge 类型、文件路径),置信度必须来自图证据,不能猜。找不到就返回 NOT_FOUND,不编答案。
注意:这个 skill 依赖 Ontoly 这个工具。需要先有 Ontoly 图(.ontoly/、SoftwareGraph.json 等),或者允许运行 ontoly build .。没有 Ontoly 的话,复制过去跑不起来。
适合谁:
- 做软件/系统类研究、需要读懂代码库的科研小组成员
- 需要做架构评审、影响分析、依赖追踪的人
- 想用图证据而不是源码搜索来理解代码的人
用法: 先把 Ontoly 环境准备好,图建好,再把 SKILL.md 内容复制到 AI 工具里用。
技能内容
SKILL.md版本与文件 ›Ontoly Software Graph
Use this skill when a coding agent needs evidence-backed software understanding from an Ontoly graph before searching repository files directly.
When to Use
- Explaining a repository architecture
- Tracing a request, route, controller, service, or dependency path
- Finding owners of services, modules, routes, configuration, or environment variables
- Reviewing dependency impact before a refactor
- Auditing dead code, cycles, unresolved imports, graph quality, or semantic coverage
- Preparing documentation, onboarding notes, or architecture review from graph evidence
Required Workflow
- Check whether an Ontoly graph already exists by looking for
.ontoly/,SoftwareGraph.json,diagnostics.json, validation reports, or an Ontoly MCP configuration. - If no graph exists and the user permits local analysis, run:
ontoly build .- Inspect graph health before answering: diagnostics, graph hash, semantic coverage, trust or quality score, framework detection, and generation timestamp.
- Prefer Ontoly CLI or MCP capabilities for graph questions instead of scanning source files first.
- Use repository search only when Ontoly cannot answer, the graph is stale, the graph is incomplete, or the user explicitly asks for source-level verification.
- Always cite graph evidence in the answer: node IDs, edge types, file paths, source locations, diagnostics, or framework analyzer output.
- State confidence from graph evidence. Do not guess confidence.
Useful Ontoly Capabilities
ExplainArchitecturefor repository and package topologyFindDependenciesfor dependency trees and direct consumersImpactAnalysisfor refactor blast radiusTraceExecutionfor request, route, and call-flow tracingFindConfigurationUsagefor configuration and environment variable usageFrameworkReportfor detected framework concepts such as modules, controllers, providers, and routesFindDeadCodefor unreachable or unused graph regions
Answer Shape
When answering, include:
- the direct answer
- graph evidence
- confidence
- diagnostics or caveats
- fallback source inspection only if needed
Example:
AuthController handles authentication.
Evidence:
- node: class:src/auth/auth.controller.ts:AuthController
- route edges: HANDLES POST /login, POST /logout
- dependency edges: USES AuthService, JwtService
Confidence: high, because the graph has controller, route, and dependency edges with source locations.Fallback Rules
- If the graph is missing, build it first when allowed.
- If graph validation fails, report the failure and use source search only to verify the affected area.
- If multiple nodes match the same name, ask for disambiguation or show the candidates with package/module context.
- If the requested concept is not in the graph, return
NOT_FOUNDwith the closest graph evidence instead of inventing an answer.
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