biswajit56546/eda-research-chain

EDA Research Chain

When to use

Use this skill when the user asks for an end-to-end research workflow, not a single isolated experiment step.

Scope

This skill orchestrates the full chain and delegates each stage to specialized skills. Global governance still follows AGENTS.md.

Stage flow

1. Bootstrap chain workspace:

python3 scripts/common/init_research_chain.py --tag <tag>

2. Knowledge exploration:

• use eda-knowledge-explorer to map local knowledge gaps,
• produce 01_knowledge/knowledge_gap_map.md.

3. Literature retrieval + local parsing:

• use eda-paper-fetch to generate download queue,
• use eda-pdf-local-summary after local PDFs are available,
• produce 02_literature/paper_download_queue.tsv and 02_literature/local_paper_summary_index.md.

4. Idea brainstorming and debate:

• use eda-idea-debate-lab,
• produce 03_idea_debate/idea_brainstorm.md and 03_idea_debate/pro_con_debate.md.

5. Hypothesis -> experiment design:

• use eda-hypothesis-experiment-designer,
• run eda-preflight-reflect before expensive submissions,
• produce 04_hypothesis_design/hypothesis_experiment_matrix.tsv.

6. Method implementation:

• use eda-method-implementer,
• produce 05_implementation/implementation_plan.md.

7. Multi-version development and integration:

• use git-version-control,
• produce 06_versioning/version_plan.md and version delta notes.

8. Validation and decision:

• execute via eda-loop,
• use validation tools/skills (delay-model-gate-evaluator, execution contract),
• produce 07_validation/validation_summary.md.

9. Retrospective:

• use eda-retro,
• produce 08_retro/research_retro.md.

10. Version milestone summary slides (conditional):

• do not generate slides for every process stage by default.
• generate a PDF summary only when a new version achieves a validated milestone improvement (e.g., first reach >=2% power reduction with non-worse area/timing, then higher milestones).
• summary should include: method delta, key conclusion, evidence table, and next-step plan.

11. Guard completeness:

python3 scripts/common/research_chain_guard.py --chain-dir <chain_dir> --out-prefix <prefix>

Hard rules

1. Do not skip the hypothesis design stage before implementation.
2. Do not promote a method without explicit validation artifact.
3. Keep each stage artifact path explicit and auditable.
4. If critical guard checks fail, block chain completion.

Reference

Load when needed:

1. references/chain-checklist.md