domains / research / idea-discovery-pipeline / idea-discovery
Both copies describe the same five-phase idea discovery pipeline (research-lit, idea-creator, novelty-check, research-review, research-refine-pipeline) with the same pilot constants and checkpoint concept. However, they disagree on the reviewer model (gpt-6-astra vs gpt-5.4), the AUTO_PROCEED semantics (non-blocking same-turn continuation vs proceed-after-silence), and the output directory (idea-stage/ vs project root). The wanshuiyin copy adds a RESUMABLE evidence gate with run_state.py and idea_discovery_gate.py, while the brycewang copy adds an explicit Phase 0 research brief loader and a Phase 0.5 reference paper summary procedure. Crowning one copy would hide the other's real steps and conflicting parameters, so the catalog should combine them and surface the conflicts.
| Repository | Path |
|---|---|
| wanshuiyin/Auto-claude-code-research-in-sleep | skills/idea-discovery/SKILL.md |
| brycewang-stanford/Auto-Empirical-Research-Skills | skills/42-wanshuiyin-ARIS/skills/idea-discovery/SKILL.md |
| Role | Repository | Path |
|---|---|---|
| peer | wanshuiyin/Auto-claude-code-research-in-sleep | skills/idea-discovery/SKILL.md |
| peer | brycewang-stanford/Auto-Empirical-Research-Skills | skills/42-wanshuiyin-ARIS/skills/idea-discovery/SKILL.md |
| adapter | wanshuiyin/Auto-claude-code-research-in-sleep | skills/skills-codex/idea-discovery/SKILL.md |
| adapter | wanshuiyin/Auto-claude-code-research-in-sleep | skills/skills-codex-gemini-review/idea-discovery/SKILL.md |
| adapter | brycewang-stanford/Auto-Empirical-Research-Skills | skills/42-wanshuiyin-ARIS/skills/skills-codex/idea-discovery/SKILL.md |
| adapter | brycewang-stanford/Auto-Empirical-Research-Skills | skills/42-wanshuiyin-ARIS/skills/skills-codex-gemini-review/idea-discovery/SKILL.md |
# Idea Discovery Pipeline Orchestrate a complete idea discovery workflow for: **$ARGUMENTS** ## Pipeline ``` /research-lit → /idea-creator → /novelty-check → /research-review → /research-refine-pipeline (survey) (brainstorm) (verify novel) (critical feedback) (refine method + plan experiments) ``` Final deliverables: a validated `IDEA_REPORT.md` with ranked ideas, plus `refine-logs/FINAL_PROPOSAL.md` and `refine-logs/EXPERIMENT_PLAN.md` for the top idea. ## Constants - PILOT_MAX_HOURS = 2 - PILOT_TIMEOUT_HOURS = 3 - MAX_PILOT_IDEAS = 3 - MAX_TOTAL_GPU_HOURS = 8 - AUTO_PROCEED = true - REVIEWER_MODEL = gpt-6-astra (wanshuiyin) / gpt-5.4 (brycewang) — see Conflicts - ARXIV_DOWNLOAD = false - COMPACT = false - REF_PAPER = false - OUTPUT_DIR = idea-stage/ (wanshuiyin) / project root (brycewang) — see Conflicts - RESUMABLE = true (wanshuiyin only) ## Checkpoint Rule Resolve AUTO_PROCEED once before Phase 0. - AUTO_PROCEED=true (wanshuiyin): non-blocking. State the result and selected next action, then continue in the same turn. Do not end the turn at a checkpoint. - AUTO_PROCEED=true (brycewang): present results; if the user does not respond, proceed with the best option. - AUTO_PROCEED=false: present options, ask the user, and end the turn. Resume only after an explicit reply. ## Phase 0: Load Research Brief (brycewang) 1. Look for `RESEARCH_BRIEF.md` in the project root or the path in `$ARGUMENTS`. 2. If found, extract problem statement, constraints, prior attempts, domain knowledge, non-goals, and existing results. 3. Use the brief as primary context; merge with `$ARGUMENTS` (brief takes priority for details). 4. If no brief exists, proceed with `$ARGUMENTS` as the research direction. ## Phase 0.5: Reference Paper Summary (when REF_PAPER is set) Skip if REF_PAPER is false. 1. If arXiv URL: invoke `/arxiv "ARXIV_ID" — download` and read the first 5 pages. 2. If local PDF: read the first 5 pages. 3. If other URL: fetch via WebFetch. 4. Generate `REF_PAPER_SUMMARY.md` with sections: Title, Authors, Venue, What They Did, Key Results, Limitations & Open Questions, Potential Improvement Directions, Codebase (if base repo is set). 5. Present a checkpoint summary to the user. ## Phase 1: Literature Survey Invoke `/research-lit "$ARGUMENTS"`. - Search arXiv, Google Scholar, Semantic Scholar. - Build a landscape map: sub-directions, approaches, open problems. - Identify structural gaps and recurring limitations. - Output a literature summary. Checkpoint: present the landscape summary and ask for confirmation or direction adjustment. ## Phase 2: Idea Generation Invoke `/idea-creator` using the literature summary and any REF_PAPER_SUMMARY.md as context. - Generate candidate ideas. - Rank by novelty, feasibility, and impact. - Output ranked ideas to `IDEA_REPORT.md#ranked-ideas`. Checkpoint: present ranked ideas. ## Phase 3: Novelty Check Invoke `/novelty-check` on the top ideas. - Verify each idea is not already published. - Record verification results in `IDEA_REPORT.md#novelty-verification`. Checkpoint: present novelty results. ## Phase 4: External Critical Review Invoke `/research-review` using REVIEWER_MODEL via Codex MCP. - Obtain critical feedback on the top ideas. - Record feedback in `IDEA_REPORT.md#external-critical-review`. Checkpoint: present review feedback. ## Phase 5: Refine and Plan Experiments Invoke `/research-refine-pipeline` on the top idea. - Refine the method. - Produce `refine-logs/FINAL_PROPOSAL.md` and `refine-logs/EXPERIMENT_PLAN.md`. - Run pilot experiments within the GPU budget constants. ## Resumable Evidence Gate (wanshuiyin only) When RESUMABLE=true: 1. Resolve `run_state.py` and `idea_discovery_gate.py` via `.aris/tools/` → `tools/` → `$ARIS_REPO/tools/` → `~/.aris/repo/tools/`. 2. Derive `<run_id>` from the direction slug and date. 3. Start the state record with `--executor <actual-model>`. 4. For each phase, mark `running` on entry and `done --artifact <path>` after the artifact is present. 5. Artifact locators: - research-lit: `idea-stage/IDEA_REPORT.md#literature-landscape` - idea-creator: `idea-stage/IDEA_REPORT.md#ranked-ideas` - novelty-check: `idea-stage/IDEA_REPORT.md#novelty-verification` - research-review: `idea-stage/IDEA_REPORT.md#external-critical-review` - research-refine-pipeline: `refine-logs/FINAL_PROPOSAL.md` 6. If either helper is unavailable, the final report is BLOCKED. ## Conflicts - **REVIEWER_MODEL**: wanshuiyin/Auto-claude-code-research-in-sleep uses `gpt-6-astra`; brycewang-stanford/Auto-Empirical-Research-Skills uses `gpt-5.4`. Choose the model available in your environment. - **AUTO_PROCEED=true semantics**: wanshuiyin treats it as non-blocking same-turn continuation; brycewang treats it as proceed-after-silence. The wanshuiyin rule is stricter and avoids ending the turn at a checkpoint. - **OUTPUT_DIR**: wanshuiyin writes to `idea-stage/`; brycewang writes to the project root. Use `idea-stage/` for consistency with the evidence gate artifact locators. - **RESUMABLE evidence gate**: present only in wanshuiyin. Include it if you need resumable, auditable runs; omit it for a simpler pipeline. - **Phase 0 research brief loader and Phase 0.5 template**: present only in brycewang. Include them to support structured briefs and reference paper summaries. ## Notes - Override defaults by appending flags, e.g., `/idea-discovery "topic" — ref paper: https://arxiv.org/abs/2406.04329` or `— compact: true`. - When COMPACT=true, write `IDEA_CANDIDATES.md` (top 3-5 ideas) at the end of the workflow for downstream skills. - When RENDER_HTML=true (wanshuiyin), render `IDEA_REPORT.md` to HTML via `/render-html` with `--no-review` at workflow end.