陌讯skills聚合平台

paper-assembly

📁 lingzhi227/claude-skills 📅 6 days ago
8
总安装量
7
周安装量
#34176
全站排名
安装命令
npx skills add https://github.com/lingzhi227/claude-skills --skill paper-assembly

Agent 安装分布

codex 6
claude-code 6
mcpjam 5
kilo 5
windsurf 5
zencoder 5

Skill 文档

Paper Assembly

Orchestrate the entire paper pipeline end-to-end with state management and checkpointing.

Input

  • $0 — Paper project directory or paper plan

References

  • Orchestration patterns and state management: ~/.claude/skills/paper-assembly/references/orchestration-patterns.md

Scripts

Check pipeline completeness

python ~/.claude/skills/paper-assembly/scripts/assembly_checker.py --dir paper/ --output checkpoint.json
python ~/.claude/skills/paper-assembly/scripts/assembly_checker.py --dir paper/ --verbose

Scans paper directory, checks 9 pipeline phases, reports missing artifacts, suggests next steps.

Workflow

Step 1: Assess Current State

  1. Scan the paper directory for existing artifacts
  2. Identify which phases are complete vs pending
  3. Build a dependency graph of remaining work

Step 2: Execute Pipeline Phases

Run phases in dependency order:

Phase Skill Input Output
1. Literature literature-search, literature-review Topic Knowledge base, BibTeX
2. Planning research-planning Knowledge base Paper structure, task list
3. Code experiment-code Plan Training/eval pipeline
4. Experiments experiment-design Code Results JSON/CSV
5. Figures figure-generation Results PNG figures
6. Tables table-generation Results LaTeX tables
7. Writing paper-writing-section All above main.tex sections
8. Citations citation-management Draft references.bib
9. Formatting latex-formatting Draft Formatted LaTeX
10. Compilation paper-compilation All PDF
11. Review self-review PDF Review scores

Step 3: State Propagation

After each phase completes:

  1. Save output artifacts to the paper directory
  2. Propagate results to downstream phases
  3. Update the progress checkpoint file

Step 4: Quality Gates

Before proceeding to the next phase:

  • Verify all required outputs exist
  • Check for consistency (e.g., all cited keys in .bib)
  • Validate figures/tables match experimental results

Step 5: Final Assembly

  1. Merge all sections into main.tex
  2. Verify all \includegraphics files exist
  3. Verify all \cite keys exist in .bib
  4. Compile to PDF
  5. Run self-review for quality check

Orchestration Patterns

Sequential Pipeline (AI-Scientist)

generate_ideas → experiments → writeup → review

Multi-Agent State Broadcasting (AgentLaboratory)

# Propagate results to all downstream agents
set_agent_attr("dataset_code", code)
set_agent_attr("results", results_json)

Copilot Mode (AgentLaboratory)

Human can intervene at any phase boundary for review/correction.

Checkpoint Format

{
  "project": "paper-name",
  "phases_completed": ["literature", "planning", "code"],
  "current_phase": "experiments",
  "artifacts": {
    "literature": "knowledge_base.json",
    "plan": "research_plan.json",
    "code": "experiments/",
    "results": null
  },
  "last_updated": "2024-01-15T10:30:00Z"
}

Rules

  • Never skip phases — each depends on previous outputs
  • Save checkpoints after every phase completion
  • Human review is recommended at phase boundaries
  • All numbers in the paper must trace to actual experiment logs
  • Re-run downstream phases if upstream changes

Related Skills

GitHub 仓库 ↗ ← 返回陌讯 Skills 聚合平台
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