| name | read-paper |
| description | Deep-dive a single paper — methodology, assumptions, implications. Triggers on "read this paper", "读论文", "explain this PDF", "arxiv.org/abs/", paper URLs, "what does this paper say", "paper deep-dive".
|
| disable-model-invocation | true |
Read Paper
Deep-dive a single paper with interactive Q&A. Outputs a structured analysis, then lets the user ask follow-up questions.
Instructions
When this skill is invoked with <input>:
Step 1: Parse input and fetch paper content
Determine input type and fetch accordingly:
| Input type | Detection | Action |
|---|
| Local PDF | <input> ends with .pdf and is a file path | Use Read tool. If PDF exceeds 20 pages, read pages 1-20 first, then ask user which sections to focus on. |
| arXiv PDF URL | <input> matches arxiv.org/pdf/ | Convert to abstract URL (replace /pdf/ with /abs/, remove .pdf suffix), then fetch with Jina Reader: curl -s "https://r.jina.ai/{abstract_url}" -H "Accept: text/markdown" |
| arXiv URL | <input> matches arxiv.org (non-PDF) | Fetch with Jina Reader: curl -s "https://r.jina.ai/{url}" -H "Accept: text/markdown" |
| Other URL | <input> starts with http:// or https:// | Try WebFetch first. If it fails or returns insufficient content, fall back to Jina Reader: curl -s "https://r.jina.ai/{url}" -H "Accept: text/markdown" |
| Pasted text | None of the above | Use <input> directly as paper content |
If fetching fails entirely, tell the user and suggest an alternative input method.
Step 2: Gather research context
Read the following files if they exist (skip silently if not found):
docs/papers/landscape.md — user's literature mapexp/summary.md — user's experiment history
Step 3: Delegate to @domain-expert
Invoke @domain-expert with this prompt:
Mode 4: Paper Deep-Dive
Paper content:
{fetched paper content}
Research context:
- Literature landscape: {landscape.md content or "not available"}
- Experiment history: {exp/summary.md content or "not available"}
Provide your structured deep-dive analysis (Methodology Skeleton, Assumptions & Limitations, Bridge Analysis), then enter interactive Q&A mode.
The user will then interact directly with domain-expert for follow-up questions. When the user says "save" / "archive" / "store" / "存档" / "保存" (with optional "as {name}"), domain-expert handles archival via its Mode 4 archive sub-flow.
