slfg
SkillDev toolsFull autonomous research workflow using swarm mode for parallel execution
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/11-James-Traina-compound-science/skills/slfg/SKILL.md and read by ahel’s review.
Swarm-enabled LFG. Run these steps in order, parallelizing where indicated. Do not stop between steps — complete every step through to the end.
Sequential Phase
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/workflows:brainstorm $ARGUMENTSGate: must produce a file indocs/brainstorms/before proceeding. -
/workflows:planGate: must produce a file indocs/plans/before proceeding. -
/workflows:work— Use swarm mode: Break the plan into independent tasks and launch parallel subagents via Task tool to build them concurrently. Each subagent handles one task from the plan. Seereferences/orchestration-patterns.mdfor parallel dispatch patterns. Gate: must produce at least one code change (committed or staged) before proceeding. If work fails with no changes, stop and report the failure.
Parallel Phase
After work completes, launch steps 4 and 5 as parallel swarm agents (both only need completed code to operate):
/workflows:review— spawn as background Task agent/workflows:compound— spawn as background Task agent
Wait for both to complete before finishing.
Output
When all steps are done, output:
Research workflow complete.
Brainstorm: [brainstorm file path]
Plan: [plan file path]
Work: [summary of implementation]
Review: [summary of findings]
Documentation: [docs/solutions/ path if created]
Start with step 1 now.
Signals
- GitHub stars
- 5k
- Forks
- 536
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
slfg- Source
- github.com/brycewang-stanford/auto-empirical-research-skills
github.com/brycewang-stanford/auto-empirical-research-skills