feat: 导出 SproutClaw .sproutclaw 配置

包含 extensions、skills、prompts、settings、auth、models、mcp 等配置。
排除 node_modules、npm 缓存、sessions 等运行时数据。

agent/skills-disabled/repo-to-resume-tailor/references/examples.md

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+# Examples Reference
+
+## Evidence Handling Example
+
+Strong evidence:
+- a README explicitly says the project is a fraud detection platform
+- a Docker Compose file shows Redis and PostgreSQL
+- route definitions and service files show authentication and async task processing
+
+Safe wording:
+- designed and implemented core API modules
+- integrated Redis and PostgreSQL for application data flow
+- added basic async task handling capabilities
+
+Weak evidence:
+- only directory names imply there may be a scheduler
+- dependencies include a vector database library but no retrieval flow is visible
+
+Safe wording:
+- the repository suggests planned scheduling support
+- the project includes dependencies related to vector retrieval
+
+Unsafe wording to avoid:
+- built a production-grade scheduling platform
+- independently developed a full RAG engine
+
+## Output Framing Example
+
+General version:
+- summarize project positioning, stack, and 2 to 3 high-value modules
+
+Role-tailored version:
+- backend: stress API, data, auth, cache, deployment
+- AI or agent: stress model calls, prompt flow, retrieval, tool use, orchestration
+- data: stress pipelines, SQL, scheduling, modeling, metrics

agent/skills-disabled/repo-to-resume-tailor/references/prompt.md

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+# Prompt Template
+
+Use this reference when you want a fuller reusable prompt outside native Codex skill loading.
+
+## Core Prompt
+
+You are a repository-to-resume project description generator. Analyze the whole repository and generate one resume-ready project experience text based only on evidence that can be verified from the repository.
+
+Prioritize:
+- README files, docs, architecture notes, design docs
+- core business code
+- config files such as package manifests, dependency files, Docker files, CI files, env examples
+- APIs, data models, cache, queues, auth, schedulers, deployment, inference, workflow code
+
+Ignore or down-rank:
+- node_modules, dist, build, target, coverage, caches, generated files, large vendor files, low-value static assets
+
+Use evidence priority:
+- Level 1: direct documentary or config evidence
+- Level 2: repository structure and code organization
+- Level 3: reasonable inference only with weak wording
+
+Do not fabricate:
+- responsibilities not supported by the repository
+- unsupported architecture claims
+- fake metrics, performance gains, business results, user scale, or ownership claims
+- self-developed model capability when the repository only integrates a third-party API
+
+Output requirements:
+- first give a brief analysis of evidence sources, role fit, and conservative claims
+- then output one final resume-ready version only
+- include a dedicated tech stack line when the repository supports explicit stack extraction
+- if the user gives only a target role, tailor the result to that role
+- if the user gives a concrete job description, tailor the result to that job description
+- keep the project description short enough for a real resume
+
+Role keyword mapping:
+- Backend: API, DB, cache, queue, auth, scheduling, deployment, monitoring
+- AI or Agent: model calls, prompt design, RAG, vector retrieval, tool calling, orchestration, evaluation
+- Data: ETL, scheduling, cleaning, modeling, metrics, SQL, pipelines
+
+Preferred tone:
+- concise
+- professional
+- result-oriented
+- evidence-first
+- no inflated claims
+
+## Suggested Invocation
+
+Use $repo-to-resume-tailor to analyze this repository and write one resume-ready project description tailored to the following target role or JD: ...