Research Lit

---
name: research-lit
description: "Search and analyze research papers, find related work, summarize key ideas. Use when user says ”find papers”, ”related work”, or ”literature search”."
argument-hint: [paper-topic-or-url]
allowed-tools: Bash(*), Read, Glob, Grep, WebSearch, WebFetch, Write, Agent, mcp__zotero__*, mcp__obsidian-vault__*
---

# Research Literature Review

使用当前执行会话完成本步；路径按步骤合同，运行清单和证据由程序生成，模型负责实质成果。

Research topic: $ARGUMENTS

## 来源与执行

搜索、读取和来源核验是领域工作；通过实际可用的工具执行并保留来源信息。进度直接向用户说明，不额外启动shell打印心跳。超时或来源缺席按实际错误处理，禁止把缺少输出猜测为宿主强杀，也不能把失败搜索记录为成功。

## Constants

- **PAPER_LIBRARY** — Local directory containing user's paper collection (PDFs). Check these paths in order:
  1. `papers/` in the current project directory
  2. `literature/` in the current project directory
  3. Custom path specified by user in `AGENTS.md` under `## Paper Library`
- **MAX_LOCAL_PAPERS = 20** — Maximum number of local PDFs to scan (read first 3 pages each). If more are found, prioritize by filename relevance to the topic.
- **ARXIV_DOWNLOAD = false** — When `true`, download top 3-5 most relevant arXiv PDFs to PAPER_LIBRARY after search. When `false` (default), only fetch metadata (title, abstract, authors) via arXiv API — no files are downloaded.
- **ARXIV_MAX_DOWNLOAD = 5** — Maximum number of PDFs to download when `ARXIV_DOWNLOAD = true`.

> 💡 Overrides:
> - `/research-lit "topic" — paper library: ~/my_papers/` — custom local PDF path
> - `/research-lit "topic" — sources: zotero, local` — only search Zotero + local PDFs
> - `/research-lit "topic" — sources: zotero` — only search Zotero
> - `/research-lit "topic" — sources: web` — only search the web (skip all local)
> - `/research-lit "topic" — arxiv download: true` — download top relevant arXiv PDFs
> - `/research-lit "topic" — arxiv download: true, max download: 10` — download up to 10 PDFs

## Data Sources

This skill checks multiple sources **in priority order**. All are optional — if a source is not configured or not requested, skip it silently.

### Source Selection

Parse `$ARGUMENTS` for a `— sources:` directive:
- **If `— sources:` is specified**: Only search the listed sources (comma-separated). Valid values: `zotero`, `obsidian`, `local`, `web`, `all`.
- **If not specified**: Default to `all` — search every available source in priority order.

Examples:
```
/research-lit "diffusion models"                        → all (default)
/research-lit "diffusion models" — sources: all         → all
/research-lit "diffusion models" — sources: zotero      → Zotero only
/research-lit "diffusion models" — sources: zotero, web → Zotero + web
/research-lit "diffusion models" — sources: local       → local PDFs only
/research-lit "topic" — sources: obsidian, local, web   → skip Zotero
```

### Source Table

| Priority | Source | ID | How to detect | What it provides |
|----------|--------|----|---------------|-----------------|
| 1 | **Zotero** (via MCP) | `zotero` | Try calling any `mcp__zotero__*` tool — if unavailable, skip | Collections, tags, annotations, PDF highlights, BibTeX, semantic search |
| 2 | **Obsidian** (via MCP) | `obsidian` | Try calling any `mcp__obsidian-vault__*` tool — if unavailable, skip | Research notes, paper summaries, tagged references, wikilinks |
| 3 | **Local PDFs** | `local` | `Glob: papers/**/*.pdf, literature/**/*.pdf` | Raw PDF content (first 3 pages) |
| 4 | **Web search** | `web` | Always available (WebSearch) | arXiv, Semantic Scholar, Google Scholar |

> **Graceful degradation**: If no MCP servers are configured, the skill works exactly as before (local PDFs + web search). Zotero and Obsidian are pure additions.

## Workflow

### Step 0a: Search Zotero Library (if available)

**Skip this step entirely if Zotero MCP is not configured.**

Try calling a Zotero MCP tool (e.g., search). If it succeeds:

1. **Search by topic**: Use the Zotero search tool to find papers matching the research topic
2. **Read collections**: Check if the user has a relevant collection/folder for this topic
3. **Extract annotations**: For highly relevant papers, pull PDF highlights and notes — these represent what the user found important
4. **Export BibTeX**: Get citation data for relevant papers (useful for `/paper-write` later)
5. **Compile results**: For each relevant Zotero entry, extract:
   - Title, authors, year, venue
   - User's annotations/highlights (if any)
   - Tags the user assigned
   - Which collection it belongs to

> 📚 Zotero annotations are gold — they show what the user personally highlighted as important, which is far more valuable than generic summaries.

### Step 0b: Search Obsidian Vault (if available)

**Skip this step entirely if Obsidian MCP is not configured.**

Try calling an Obsidian MCP tool (e.g., search). If it succeeds:

1. **Search vault**: Search for notes related to the research topic
2. **Check tags**: Look for notes tagged with relevant topics (e.g., `#diffusion-models`, `#paper-review`)
3. **Read research notes**: For relevant notes, extract the user's own summaries and insights
4. **Follow links**: If notes link to other relevant notes (wikilinks), follow them for additional context
5. **Compile results**: For each relevant note:
   - Note title and path
   - User's summary/insights
   - Links to other notes (research graph)
   - Any frontmatter metadata (paper URL, status, rating)

> 📝 Obsidian notes represent the user's **processed understanding** — more valuable than raw paper content for understanding their perspective.

### Step 0c: Scan Local Paper Library

Before searching online, check if the user already has relevant papers locally:

1. **Locate library**: Check PAPER_LIBRARY paths for PDF files
   ```
   Glob: papers/**/*.pdf, literature/**/*.pdf
   ```

2. **De-duplicate against Zotero**: If Step 0a found papers, skip any local PDFs already covered by Zotero results (match by filename or title).

3. **Filter by relevance**: Match filenames and first-page content against the research topic. Skip clearly unrelated papers.

4. **Summarize relevant papers**: For each relevant local PDF (up to MAX_LOCAL_PAPERS):
   - Read first 3 pages (title, abstract, intro)
   - Extract: title, authors, year, core contribution, relevance to topic
   - Flag papers that are directly related vs tangentially related

5. **Build local knowledge base**: Compile summaries into a "papers you already have" section. This becomes the starting point — external search fills the gaps.

> 📚 If no local papers are found, skip to Step 1. If the user has a comprehensive local collection, the external search can be more targeted (focus on what's missing).

### Step 1: Search (external)

**⛔ 优先使用 `$SCHOLAR_SCRIPT` 搜索（自动调用 AMiner + Semantic Scholar + DBLP + CrossRef，返回真实论文）：**

```bash
PYTHON=""; for _c in "$MH_PYTHON" python python3; do [ -z "$_c" ] && continue; if $_c -c "import sys" >/dev/null 2>&1; then PYTHON="$_c"; break; fi; done; [ -z "$PYTHON" ] && PYTHON=python
# 搜索论文 + 获取 BibTeX（推荐，一次调用完成所有工作）
$PYTHON "$SCHOLAR_SCRIPT" bibtex "RESEARCH_TOPIC_KEYWORDS" --max 10
# 中文主题同样支持（AMiner 自动返回中文标题 + 作者 + 年份 + DOI）
$PYTHON "$SCHOLAR_SCRIPT" bibtex "中文研究主题" --max 10
```

- 中文 query → AMiner 免费搜索（返回真实中文论文，不会出现假文献）
- 英文 query → Semantic Scholar 优先，AMiner 补充
- 所有结果都有 DOI 或 AMiner ID，可验证真实性
- **De-duplicate**: Skip papers already found in Zotero, Obsidian, or local library

**Result quality check (mandatory):**
1. **Inspect `match_label`**: `"good"` → use directly; `"partial"` → verify title actually matches your topic; `"low"` → likely wrong paper, retry with better keywords or fall back to WebSearch.
2. `match_score < 0.3` is unreliable; do not blindly trust.
3. `bibtex_source="auto"` entries need DOI verification before being used.

**补充搜索**：如果 `$SCHOLAR_SCRIPT` 结果不足或大部分 `match_label="low"`，再用以下方式补充：
- Use WebSearch to find recent papers on the topic
- Check arXiv, Google Scholar
- Focus on papers from last 2 years unless studying foundational work

**arXiv API search** (always runs, no download by default):

Locate the fetch script and search arXiv directly:
```bash
# Try to find arxiv_fetch.py
SCRIPT=$(find tools/ -name "arxiv_fetch.py" 2>/dev/null | head -1)

# Search arXiv API for structured results (title, abstract, authors, categories)
# Use python3 or python depending on what's available
PYTHON=""; for _c in "$MH_PYTHON" python python3; do [ -z "$_c" ] && continue; if $_c -c "import sys" >/dev/null 2>&1; then PYTHON="$_c"; break; fi; done; [ -z "$PYTHON" ] && PYTHON=python
$PYTHON "$SCRIPT" search "QUERY" --max 10
```

If `arxiv_fetch.py` is not found, fall back to WebSearch for arXiv (same as before).

The arXiv API returns structured metadata (title, abstract, full author list, categories, dates) — richer than WebSearch snippets. Merge these results with WebSearch findings and de-duplicate.

**Optional PDF download** (only when `ARXIV_DOWNLOAD = true`):

After all sources are searched and papers are ranked by relevance:
```bash
# Download top N most relevant arXiv papers
$PYTHON "$SCRIPT" download ARXIV_ID --dir papers/
```
- Only download papers ranked in the top ARXIV_MAX_DOWNLOAD by relevance
- Skip papers already in the local library
- 1-second delay between downloads (rate limiting)
- Verify each PDF > 10 KB

### Step 2: Analyze Each Paper
For each relevant paper (from all sources), extract:
- **Problem**: What gap does it address?
- **Method**: Core technical contribution (1-2 sentences)
- **Results**: Key numbers/claims
- **Relevance**: How does it relate to our work?
- **Source**: Where we found it (Zotero/Obsidian/local/web) — helps user know what they already have vs what's new

### Step 3: Synthesize
- Group papers by approach/theme
- Identify consensus vs disagreements in the field
- Find gaps that our work could fill
- If Obsidian notes exist, incorporate the user's own insights into the synthesis

### Step 4: Output
Write the current step's declared output files. The standard survey is **`literature_review.md`** plus **`references.bib`**. When the action also declares `LIT_EVIDENCE.json` and `search_evidence/`, record the actual query/source/retrieval outcome and save source responses or excerpts with provenance there; never fabricate records to satisfy the contract. Present the survey as a structured literature table:

```
| Paper | Venue | Method | Key Result | Relevance to Us | Source |
|-------|-------|--------|------------|-----------------|--------|
```

Plus a narrative summary of the landscape (3-5 paragraphs).

If Zotero BibTeX was exported, include a `references.bib` snippet for direct use in paper writing. Also save a standalone **`references.bib`** file in the project root with all collected BibTeX entries.

### Step 5: Save (if requested)
- Save paper PDFs to `literature/` or `papers/`
- Update related work notes in project memory
- If Obsidian is available, optionally create a literature review note in the vault

## Key Rules
- **⛔ File writing strategy (prevent both failure modes):**
  - literature_review.md is often long (>150 lines with many citations) → **Write the first section with Write tool (ensures file exists), then `cat << 'EOF' >> literature_review.md` to append remaining sections**
  - If content is short (<150 lines) → just use Write directly
  - **NEVER end_turn without writing the review** — even if search results are limited, write what you have
- Always include paper citations (authors, year, venue)
- Distinguish between peer-reviewed and preprints
- Be honest about limitations of each paper
- Note if a paper directly competes with or supports our approach
- **Never fail because a MCP server is not configured** — always fall back gracefully to the next data source
- Zotero/Obsidian tools may have different names depending on how the user configured the MCP server (e.g., `mcp__zotero__search` or `mcp__zotero-mcp__search_items`). Try the most common patterns and adapt.

产出结构、存在性和最低完整性由 `finish` 按模板中的 `output_contract` 自动核验；修复返回的具体问题，不复制执行验证脚本。