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Research
Skill

/deep-research

Conduct systematic academic literature reviews in 6 phases, producing structured notes, a curated paper database, and a synthesized final report. Output is organized by phase for clarity.

From plugin
agent-research-skills
26531 skills1 command
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill deep-research --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deep-research

Context preview

The summary Claude sees to decide when to auto-load this skill.

Conduct systematic academic literature reviews in 6 phases, producing structured notes, a curated paper database, and a synthesized final report. Output is organized by phase for clarity.

SKILL.md

deep-research.SKILL.md
name: deep-research
description: Conduct systematic academic literature reviews in 6 phases, producing structured notes, a curated paper database, and a synthesized final report. Output is organized by phase for clarity.
argument-hint: [topic]

Deep Research Skill

Trigger

Activate this skill when the user wants to:

  • "Research a topic", "literature review", "find papers about", "survey papers on"
  • "Deep dive into [topic]", "what's the state of the art in [topic]"
  • Uses `/research <topic>` slash command

Overview

This skill conducts systematic academic literature reviews in 6 phases, producing structured notes, a curated paper database, and a synthesized final report. Output is organized **by phase** for clarity.

**Installation**: `~/.claude/skills/deep-research/` — scripts, references, and this skill definition. **Output**: `.//Users/lingzhi/Code/deep-research-output/{slug}/` relative to the current working directory.

CRITICAL: Strict Sequential Phase Execution

**You MUST execute all 6 phases in strict order: 1 → 2 → 3 → 4 → 5 → 6. NEVER skip any phase.**

This is the single most important rule of this skill. Violations include:

  • ❌ Jumping from Phase 2 to Phase 5/6 (skipping Deep Dive and Code)
  • ❌ Writing synthesis or report before completing Phase 3 deep reading
  • ❌ Producing a final report based only on abstracts/titles from search results
  • ❌ Combining or merging phases (e.g., doing "Phase 3-5 together")

Phase Gate Protocol

Before starting Phase N+1, you MUST verify that Phase N's **required output files** exist on disk. If they don't exist, you have NOT completed that phase.

| Phase | Gate: Required Output Files | |-------|---------------------------| | 1 → 2 | `phase1_frontier/frontier.md` exists AND contains ≥10 papers | | 2 → 3 | `phase2_survey/survey.md` exists AND `paper_db.jsonl` has 35-80 papers | | 3 → 4 | `phase3_deep_dive/selection.md` AND `phase3_deep_dive/deep_dive.md` exist AND deep_dive.md contains detailed notes for ≥8 papers | | 4 → 5 | `phase4_code/code_repos.md` exists AND contains ≥3 repositories | | 5 → 6 | `phase5_synthesis/synthesis.md` AND `phase5_synthesis/gaps.md` exist |

**After completing each phase, print a phase completion checkpoint:**

✅ Phase N complete. Output: [list files written]. Proceeding to Phase N+1.

Why Every Phase Matters

  • **Phase 3 (Deep Dive)** is where you actually READ papers — without it, your synthesis is superficial and based only on abstracts
  • **Phase 4 (Code & Tools)** grounds the research in practical implementations — without it, you miss the open-source ecosystem
  • **Phase 5 (Synthesis)** requires deep knowledge from Phase 3 — you cannot synthesize papers you haven't read
  • **Phase 6 (Report)** assembles content from ALL prior phases — it should cite specific findings from Phase 3 notes

Paper Quality Policy

**Peer-reviewed conference papers take priority over arXiv preprints.** Many arXiv papers have not undergone peer review and may contain unverified claims.

Source Priority (highest to lowest)

1. **Top AI conferences**: NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL, AAAI, IJCAI, CVPR, KDD, CoRL 2. **Peer-reviewed journals**: JMLR, TACL, Nature, Science, etc. 3. **Workshop papers**: NeurIPS/ICML workshops (lower bar but still reviewed) 4. **arXiv preprints with high citations**: Likely high-quality but unverified 5. **Recent arXiv preprints**: Use cautiously, note "preprint" status explicitly

When to Use arXiv Papers

  • As **supplementary** evidence alongside peer-reviewed work
  • For **very recent** results (< 3 months old) not yet at conferences
  • When a peer-reviewed version doesn't exist yet — note `(preprint)` in citations
  • For **survey/review** papers (these are useful even without peer review)

Search Tools (by priority)

1. paper_finder (primary — conference papers only)

**Location**: `/Users/lingzhi/Code/documents/tool/paper_finder/paper_finder.py`

Searches ai-paper-finder.info (HuggingFace Space) for published conference papers. Supports filtering by conference + year. Outputs JSONL with BibTeX.

python /Users/lingzhi/Code/documents/tool/paper_finder/paper_finder.py --mode scrape --config <config.yaml>
python /Users/lingzhi/Code/documents/tool/paper_finder/paper_finder.py --mode download --jsonl <results.jsonl>
python /Users/lingzhi/Code/documents/tool/paper_finder/paper_finder.py --list-venues

Config example:

searches:
  - query: "long horizon reasoning agent"
    num_results: 100
    venues:
      neurips: [2024, 2025]
      iclr: [2024, 2025, 2026]
      icml: [2024, 2025]
output:
  root: /Users/lingzhi/Code/deep-research-output/{slug}/phase1_frontier/search_results
  overwrite: true

2. search_semantic_scholar.py (supplementary — citation data + broader coverage)

**Location**: `/Users/lingzhi/.claude/skills/deep-research/scripts/search_semantic_scholar.py` Supports `--peer-reviewed-only` and `--top-conferences` filters. API key: `/Users/lingzhi/Code/keys.md` (field `S2_API_Key`)

3. search_arxiv.py (supplementary — latest preprints)

**Location**: `/Users/lingzhi/.claude/skills/deep-research/scripts/search_arxiv.py` For searching recent papers not yet published at conferences. Mark citations with `(preprint)`.

Other Scripts

| Script | Location | Key Flags | |--------|----------|-----------| | `download_papers.py` | `~/.claude/skills/deep-research/scripts/` | `--jsonl`, `--output-dir`, `--max-downloads`, `--sort-by-citations` | | `extract_pdf.py` | `~/.claude/skills/deep-research/scripts/` | `--pdf`, `--pdf-dir`, `--output-dir`, `--sections-only` | | `paper_db.py` | `~/.claude/skills/deep-research/scripts/` | subcommands: `merge`, `search`, `filter`, `tag`, `stats`, `add`, `export` | | `bibtex_manager.py` | `~/.claude/skills/deep-research/scripts/` | `--jsonl`, `--output`, `--keys-only` | | `compile_report.py` | `~/.claude/skills/deep-research/scripts/` | `--topic-dir` |

WebFetch Mode (no Bash)

1. **Paper disc

Read more
Ships withagent-research-skills

31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.

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Repo: lingzhi227/agent-research-skills

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