/idea-discovery

name: idea-discovery
description: "Workflow 1: Full idea discovery pipeline to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow."
argument-hint: "[research-direction]"
allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch, Skill, mcp__codex__codex, mcp__codex__codex-reply

Workflow 1: Idea Discovery Pipeline

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md): > resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP) > with `reviewer_route.py` through the canonical helper resolver, preserving this > slot's tier, fresh contexts, source/image inputs and deterministic gates. > Codex examples/pins below apply only to `backend=codex`; other routes use their > own first-call/reply contract. Save the route and actual returned identity; > unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual > families/completion/scope. Forward invocation reviewer/model/effort overrides > to reviewer-bearing children. Generation workers are unchanged.

Orchestrate a complete idea discovery workflow for: **$ARGUMENTS**

Overview

This skill chains sub-skills into a single automated pipeline:

/research-lit → /idea-creator → /novelty-check → /research-review → /research-refine-pipeline
  (survey)      (brainstorm)    (verify novel)    (critical feedback)  (refine method + plan experiments)

Each phase builds on the previous one's output. The final deliverables are a validated `idea-stage/IDEA_REPORT.md` with ranked ideas, plus a refined proposal (`refine-logs/FINAL_PROPOSAL.md`) and experiment plan (`refine-logs/EXPERIMENT_PLAN.md`) for the top idea.

Constants

• **PILOT_MAX_HOURS = 2** — Skip any pilot experiment estimated to take > 2 hours per GPU. Flag as "needs manual pilot" in the report.
• **PILOT_TIMEOUT_HOURS = 3** — Hard timeout: kill any running pilot that exceeds 3 hours. Collect partial results if available.
• **MAX_PILOT_IDEAS = 3** — Run pilots for at most 3 top ideas in parallel. Additional ideas are validated on paper only.
• **MAX_TOTAL_GPU_HOURS = 8** — Total GPU budget across all pilots. If exceeded, skip remaining pilots and note in report.
• **AUTO_PROCEED = true** — When `true`, checkpoints are informational: report the selected option and continue in the same turn. Set to `false` to ask for explicit user confirmation and end the turn at each selection checkpoint.
• **REVIEWER_MODEL = `gpt-6-astra`** — Model used via Codex MCP. For `backend=codex`, use an OpenAI model (e.g., `gpt-6-astra`, `gpt-6.1-sol`). Passed to sub-skills.
• **OUTPUT_DIR = `idea-stage/`** — All idea-stage outputs go here. Create the directory if it doesn't exist.
• **ARXIV_DOWNLOAD = false** — When `true`, `/research-lit` downloads the top relevant arXiv PDFs during Phase 1. When `false` (default), only fetches metadata. Passed through to `/research-lit`.
• **COMPACT = false** — When `true`, generate compact summary files for short-context models and session recovery. Writes `idea-stage/IDEA_CANDIDATES.md` (top 3-5 ideas only) at the end of this workflow. Downstream skills read this instead of the full `idea-stage/IDEA_REPORT.md`.
• **RENDER_HTML = true** — When `true` (default), auto-render `idea-stage/IDEA_REPORT.md` to HTML at workflow end via `/render-html`. Uses `--no-review` (the source MD already went through novelty + cross-model review during Phase 3). Set `false` to skip, or pass `— render html: false`.
• **REF_PAPER = false** — Reference paper to base ideas on. Accepts: local PDF path, arXiv URL, or any paper URL. When set, the paper is summarized first (`idea-stage/REF_PAPER_SUMMARY.md`), then idea generation uses it as context. Combine with `base repo` for "improve this paper with this codebase" workflows.
• **RESUMABLE = true** — Record stage evidence under `.aris/runs/<run_id>.json` and require a deterministic evidence gate before declaring the final report complete.

> 💡 These are defaults. Override by telling the skill, e.g., `/idea-discovery "topic" — ref paper: https://arxiv.org/abs/2406.04329` or `/idea-discovery "topic" — compact: true`.

Checkpoint execution rule

Resolve `AUTO_PROCEED` once from `$ARGUMENTS` before Phase 0 and keep that mode for the entire workflow.

• **`AUTO_PROCEED=true` is non-blocking.** A checkpoint is a progress update,

not a question. State the result and the automatically selected next action, then continue executing in the **same turn**. Do not ask for confirmation, request user input, sleep, wait for silence, or end the turn at a checkpoint.

• **`AUTO_PROCEED=false` is blocking.** Present the options, ask the user, and

end the turn. Resume only after an explicit reply.

Never implement auto-proceed as “ask, then continue if there is no response.” Once a turn ends, silence cannot resume the workflow. The user can still interrupt a non-blocking run at any time.

This rule governs only `AUTO_PROCEED`-controlled selection checkpoints. If the user explicitly enables a Feishu **interactive** gate, that external approval or reply is an intentional blocking exception; wait for that user-controlled gate rather than treating it as a silence timeout. Feishu off/push-only modes remain non-blocking under `AUTO_PROCEED=true`.

Per-stage evidence gate (`RESUMABLE = true`)

Resolve `run_state.py` and `idea_discovery_gate.py` through the same canonical helper chain used by `/research-pipeline`: `.aris/tools/` → `tools/` → `$ARIS_REPO/tools/` → `~/.aris/repo/tools/`. If either helper is unavailable, the final report is `BLOCKED`; do not silently continue without a state record.

For a new run, derive `<run_id>` from the direction slug and date, then start this ordered state record with `--executor <actual-Claude-model>` (for example, `claude-sonnet-4.5`):

research-lit,idea-creat