ReMe/reme/steps/cookbook/daily_paper/select.yaml
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feat: add daily paper cookbook and DingTalk agent integration (#385)
* feat(daily-paper): add daily paper cookbook workflow with schema and tests

- Introduce daily paper schema types (DailyBriefOutput, PaperInfo, PaperNoteOutput, etc.)
- Create daily paper cookbook module with analyze, collect, digest, rank, and select steps
- Add cookbook entry point and integrate into main steps module
- Replace job config export with daily brief output in schema exports
- Add comprehensive unit tests covering pipeline, filtering, and output generation
- Update dependencies including openai-codex and pypdf packages
- Configure standalone daily paper cron job with proper scheduling and routing

* test(daily_paper): update tests to use Claude Code wrapper exclusively

- Add test to verify web search is disallowed by default in Claude Code
- Update imports to include DailyBriefOutput, PaperNoteOutput, and PaperSelection schemas
- Change test name from standalone_config_has_backend_split to reflect Claude Code only usage
- Remove default agent wrapper and configure all steps to use Claude Code wrapper
- Rename select_wrapper to cc_wrapper for clarity and consistency
- Remove duplicate Claude Code wrapper initialization
- Update test assertions to verify output schema usage matches expected sequence
- Remove unused as_llm component from standalone configuration test

* refactor(agent-wrapper): simplify skill resolution logic across all wrappers

- Replace duplicate skill resolution code with centralized _resolve_project_skills method
- Add project_path property with configurable relative path resolution
- Introduce proper validation for skill names and directory existence
- Change Codex wrapper to use project_path instead of workspace_path for skills
- Add SKILL.md requirement validation for project skills
- Remove redundant skill processing logic from individual wrappers

* feat(daily_paper): add daily paper workflow with PDF analysis and brief generation

- Implement shared state management and file helpers for daily-paper steps
- Add PDF download and text extraction capabilities with arXiv integration
- Create paper collection step with Hugging Face weekly/monthly rankings
- Build ranking system using reciprocal-rank fusion with memory keyword scoring
- Add Claude Code integration for paper analysis and detailed note generation
- Implement digest step to create final five-minute brief from detailed notes
- Add configuration for standalone daily cookbook application with cron scheduling
- Create typed schema for paper information, selection, and output formats
- Add atomic file writing with temporary file safety mechanisms
- Implement exclusion logic for previously recommended papers and daily filters

* feat(daily_paper): add DingTalk notification integration and enhance logging

- Integrate DingTalk markdown send step to notify groups about daily paper briefs
- Add comprehensive logging throughout daily paper workflow including start/finish events
- Update daily paper analysis prompt to include code repository context requirement
- Configure DingTalk notification in daily_cookbook.yaml with app credentials
- Add dingtalk-stream dependency for proactive message API integration
- Enhance daily paper README with DingTalk notification section and updated flow chart
- Implement detailed logging for each step including paper processing and agent calls
- Add test coverage for DingTalk markdown sending functionality and configuration
- Update pre-commit config to exclude skills directory from checks
- Add .claude/skills to gitignore for local development environment

* refactor(dingtalk): move dingtalk_stream import to local scope and improve code safety

- Moved global dingtalk_stream import to local scope in send.py to avoid eager loading
- Added dynamic import with error handling for optional dependency cases
- Updated test suite to verify lazy loading behavior works correctly
- Fixed markdown title generation by using safe variable naming in wait.py
- Enhanced test coverage for arxiv PDF download caching functionality
- Updated application context initialization with proper resource directory configuration
- Modified paper metadata to include source PDF path reference in output files

* refactor(daily_paper): remove manifest system and store selection metadata in digest files

- Remove JSON manifest creation and storage functionality
- Store selection data directly in digest file frontmatter instead of separate manifest files
- Add load_saved_selection method to rebuild selection from digest and paper-note metadata
- Update README documentation to reflect new cookbook workflow architecture
- Modify test cases to verify selection metadata in digest files instead of manifest JSON
- Remove unused json import from multiple daily paper modules
- Integrate PaperSelection schema for proper data validation in stored metadata

* docs(daily_paper): add bilingual cookbook guides
2026-07-22 19:17:01 +08:00

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select_user: |
你是 AI 研究论文编辑。请从以下候选中选择恰好 {top_k} 篇最值得深入阅读的论文,并另外给出至多 3 个候补 ID。
选择应兼顾研究价值、技术新颖性、潜在影响和可读性。融合分与榜单排名是重要依据,但不是唯一依据。
与大模型 Agent 长期记忆、记忆检索、记忆整合、持续学习、个性化和上下文管理直接相关的高质量论文应优先考虑。
只能选择输入候选集合中的 arXiv ID不得编造论文或事实。输出简洁、可核验的选择理由。
要求:
1. selected 的 rank 必须从 1 到 {top_k} 连续排列。
2. arxiv_id 必须逐字复制候选数据中的值,不能重复。
3. reason 说明具体选择依据,不要只复述标题。
4. memory_relevance 评价论文与大模型/Agent 长期记忆的相关程度。
5. selection_reasoning 是面向读者的简短决策摘要,不要输出隐含的逐步思维过程。
上一次校验反馈:{retry_feedback}
# 候选论文
{candidates}