name: academic-repro description: Run AutoForge as an academic research workflow engine for paper inference, reproduction planning, evidence-pack generation, and long-running research jobs.
Academic Reproduction with AutoForge
Use this skill when the user wants to:
- infer likely papers from a research goal
- reproduce a paper or build a reproduction brief
- extract claims, datasets, metrics, and environment assumptions
- queue a long-running research workflow and monitor it over time
Preferred workflow:
- If needed, start the durable runtime:
autoforgeai daemon start
- For paper discovery or reproduction artifacts:
autoforgeai paper infer "<goal>"autoforgeai paper reproduce "<goal>" --top-k 5 --pick 1
- For long-running work, prefer queue/watch over one-shot execution:
autoforgeai queue "<research objective>"autoforgeai watch <project_id>autoforgeai msg <project_id> "<new constraint or direction>"
- Preserve and summarize the resulting artifacts:
candidate.jsonreproduction_brief.mdgeneration_prompt.txtpaper_signals.jsonverification_plan.jsonenvironment_spec.jsonrun_manifest.jsonrepro_report.json
Operational guidance:
- Use the daemon path when the research workflow may take more than one interactive Claude turn.
- Prefer evidence and artifact paths over vague summaries.
- Call out whether the result is reproduced, partially reproduced, or not reproduced.
- If the user wants interactive correction mid-run, use
msgorunpauserather than restarting from scratch.