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research-workflow

Dynamic research workflow management with self-reflection and backtracking

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Quellinformationen

Repository
openags/auto-researcher
Letzte Quellaktivität
20. März 2026 um 18:36
Erkannte Sprache von SKILL.md
Englisch
Sterne
9
Forks
2

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Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
research-workflow
description
Dynamic research workflow management with self-reflection and backtracking
roles
["ags"]
tools
["dispatch_agent","check_progress","ask_user"]
triggers
["research","workflow","pipeline","run project","start research","always"]
version
1.0.0
## Research Workflow Management When managing a research project, follow this adaptive workflow: ### Stage Progression (typical order, but flexible) 1. **Literature Review** → Understand the field - Dispatch: `dispatch_agent(role="literature", task="...")` - Expected output: Review notes in `literature/notes/`, BibTeX in references - Proceed when: Review covers key related work with cited papers 2. **Research Proposal** → Define the research question - Dispatch: `dispatch_agent(role="proposer", task="...")` - Expected output: Proposal document in `proposal/ideas/` - Proceed when: Clear hypotheses, methodology, and expected outcomes 3. **Experiments** → Validate the hypothesis - Dispatch: `dispatch_agent(role="experimenter", task="...")` - Expected output: Code in `experiments/code/`, results in `experiments/results/` - Proceed when: Code runs successfully and produces meaningful results - **Common backtrack**: If results don't support hypothesis → re-examine proposal 4. **Manuscript** → Write the paper - Dispatch: `dispatch_agent(role="writer", task="...")` - Expected output: LaTeX in `manuscript/main.tex` - Proceed when: All sections drafted with citations 5. **Peer Review** → Quality check - Dispatch: `dispatch_agent(role="reviewer", task="...")` - Expected output: Structured review with scores - **Common backtrack**: If scores < 6/10 → address specific feedback ### Self-Reflection Protocol After each agent completes, reflect on: - **Quality**: Is the output good enough for the next stage? - **Consistency**: Does it align with previous stages? - **Completeness**: Are there gaps that need filling? If issues are found, you have three options: 1. **Fix**: Dispatch the same agent with more specific instructions 2. **Backtrack**: Go to an earlier stage to address root causes 3. **Consult**: Use `ask_user` to get human guidance
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