ablation-planner
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
$ npx -y skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill idea-creator --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/idea-creatorContext preview
The summary Claude sees to decide when to auto-load this skill.
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
name: idea-creator description: Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions. argument-hint: "[research-direction]" allowed-tools: Bash(*), Read, Write, Grep, Glob, WebSearch, WebFetch, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply, mcp__manual_review__review, mcp__manual_review__review_reply
Generate publishable research ideas for: $ARGUMENTS
Given a broad research direction from the user, systematically generate, validate, and rank concrete research ideas. Standalone, Phase 1's landscape survey is **inline** (WebSearch — it does not invoke `/research-lit`); Phases 4-5 invoke `/novelty-check`, `/run-experiment`, and `/monitor-experiment` for validation and pilots. For the full sub-skill pipeline (`/research-lit` → idea generation → `/novelty-check` → `/research-review`), run `/idea-discovery` (Workflow 1), which orchestrates this skill.
> 💡 Override via argument, e.g., `/idea-creator "topic" — pilot budget: 4h per idea, 20h total`.
When calling the reviewer for idea evaluation, branch on REVIEWER_BACKEND:
**If REVIEWER_BACKEND = `codex`:** Use `mcp__codex__codex` for new review threads. Use `mcp__codex__codex-reply` for follow-up rounds (reuse threadId).
**If REVIEWER_BACKEND = `manual`:** Use `mcp__manual_review__review` for new review threads with: prompt: [exact same prompt that would go to Codex] config: {"model_reasoning_effort": "xhigh", "executor_model": "<actual executor model>", "require_reviewer_model": true} Save the returned `threadId`. Use `mcp__manual_review__review_reply` for follow-up rounds with: threadId: [saved manual-review threadId] prompt: [follow-up prompt] config: {"model_reasoning_effort": "xhigh", "executor_model": "<actual executor model>", "require_reviewer_model": true}
Content fidelity: the manual reviewer should see the same substantive bundle content Codex would read. If the manual UI supports file upload / attachment, reuse the same bundle file; otherwise paste the bundle contents inline because remote web UIs cannot read your local filesystem paths. Review tracing applies equally to both backends.
A verdict-bearing manual response MUST begin with `Reviewer-Model: <exact-model-id>` — pass the model THIS session is actually running as in `executor_model`. Missing, unknown, or same-family identity cannot acquit; emit `REVIEW_UNAVAILABLE` rather than guessing. If the executor model cannot be named, manual review's cross-family claim is unprovable — say so in the report instead of asserting it.
**Skip this phase entirely if `research-wiki/` does not exist.**
If `research-wiki/` exists, resolve the canonical helper using the shared resolution chain (see `../research-wiki/SKILL.md` for the contract):
cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
ARIS_REPO="${ARIS_REPO:-}"
ARIS_HOME="${HOME:-}"
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
fi
if [ -z "${ARIS_REPO:-}" ] && [ -n "$ARIS_HOME" ] && [ -f "$ARIS_HOME/.aris/repo" ]; then
ARIS_REPO=$(cat "$ARIS_HOME/.aris/repo" 2>/dev/null) || true
fi
WIKI_SCRIPT=".aris/tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || WIKI_SCRIPT="tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || { [ -n "${ARIS_REPO:-}" ] && WIKI_SCRIPT="$ARIS_REPO/tools/research_wiki.py"; }
[ -f "$WIKI_SCRIPT" ] || {
echo "WARN: research_wiki.py not found at .aris/tools/, tools/, \$ARIS_REPO/tools/, or via ~/.aris/repo." >&2
echo " The idea-creation primary output (idea ranking) will still be produced." >&2
echo " Wiki writes and query_pack rebuilds will be skipped; a fresh cached pack may still be loaded through the scanner." >&2
echo " Fix: rerun 'bash tools/install_aris.sh' or 'smart_update.sh' (refreshes ~/.aris/repo), export ARIS_REPO, or 'cp <ARIS-repo>/tools/research_wiki.py tools/'." >&2
WIKI_SCRIPT=""
}
THREAT_SCANNER=".aris/tools/threat_scan.py"
[ -f "$THREAT_SCANNER" ] || THREAT_SCANNER="tools/threat_scan.py"
[ -f "$THREAT_SCANNER" ] || { [ -n "${ARIS_REPO:-}" ] && THREAT_SCANNER="$ARIS_REPO/tools/threat_scan.py"; }
[ -f "$THREAT_SCANNER" ] || THREAT_SCANNER=""
# ARIS_QUERY_PACK_SCAN_START -- exercised by
# tests/test_idea_creator_query_pack_scan.py; keep both skill mirrors identical.
aris_scan_query_pack() {
l· · · · · · -orange?style=flat) · · 💬 Join Community · 💡 Use ARIS as a skill-based workflow in Claude Code / Codex CLI / Cursor / Trae / Antigravity / GitHub Copilot CLI / OpenClaw / DeepSeek Harness, or get the full experience with the standalone ARIS-Code
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes…
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to…
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper…
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says \"改论文\", \"improve paper\",…
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop…