Orchestrate the full paper pipeline end-to-end. Manage state propagation between phases (literature → plan → code → experiments → figures → tables → writing →…
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
Scan the paper directory for existing artifacts
Identify which phases are complete vs pending
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:
Save output artifacts to the paper directory
Propagate results to downstream phases
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
Merge all sections into main.tex
Verify all \includegraphics files exist
Verify all \cite keys exist in .bib
Compile to PDF
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
Upstream: all other skills (this is the orchestrator)
Downstream: paper-compilation, self-review
See also: research-planningdon't have the plugin yet? install it then click "run inline in claude" again.