# Paper Reading > Read a robotics/AI paper, blog post, or tech report from a URL (or local PDF) and write a structured deep-dive note into papers/notes/, then update the global categorized index at papers/INDEX.md. Use whenever the user posts a paper URL, says "read this paper", "add this paper", "记录这篇论文", or asks to re-index / re-categorize the paper library. - Skill: `fangyi-chen/paper-reading` (Agent Skill) - Install (CLI): `npx skillmds@latest add fangyi-chen/paper-reading` - Raw SKILL.md: https://api.skillmd.com/api/skills/fangyi-chen/paper-reading/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Docs & Writing - Author: fangyi-chen (https://skillmd.com/u/fangyi-chen) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/fangyi-chen/paper-reading --- # Paper Reading Workflow Turn a paper URL into a durable, structured note plus an up-to-date global index. This is the standard intake pipeline for this repo's learning log. ## Layout ``` papers/ INDEX.md # global categorized index of ALL papers — always update TEMPLATE.md # canonical note template notes/ YYYY-MM-DD-slug.md # one file per paper ``` `YYYY-MM-DD` is the paper's own publication date (not today's date). `slug` is a kebab-case short name, e.g. `2026-08-19-gen-1.5-one-shot-learners.md`. ## Step 1 — Fetch the source, faithfully Do **not** work from memory or from a single lossy summary. Get the real text. 1. Try `WebFetch` first for a quick orientation. 2. Then get the raw text so no numbers are lost. Preferred: ```bash curl -sL -A "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 Chrome/125.0 Safari/537.36" "" -o "$SCRATCH/page.html" ``` then strip tags to text (drop `script`/`style`/`svg`/`noscript`, turn block-close tags into newlines, unescape entities) and read the result. 3. arXiv: prefer the `https://arxiv.org/abs/` page for the abstract, and `https://arxiv.org/pdf/` (read with the Read tool's `pages` param) for the full body. `ar5iv.labs.arxiv.org/html/` is a good HTML fallback. 4. Local PDF: read it with the Read tool using `pages` ranges. 5. If a section genuinely isn't in the source (common for company blog posts that hide model size or data scale), write **"Not disclosed"** — never invent it. ## Step 2 — Write the note Copy `papers/TEMPLATE.md` and fill every section. Rules: - **Quote numbers exactly** as the source states them, including error bars (`59% (±10% std. dev.)`), and say what they are measured over. - Mark your own commentary clearly. Anything that is your inference rather than the authors' claim goes under *Insight & My Take* or is prefixed "**(my read)**". - Keep the *Open Questions* and *Insight* sections opinionated and concrete — they are the part that is worth rereading in six months. - Record the reference list only when it is short and load-bearing; otherwise list the 5–10 references that actually matter for understanding the work. - Front-matter of each note is YAML and drives the index: ```yaml --- title: ... authors: ... venue: ... # arXiv / CoRL 2026 / company blog / ... date: YYYY-MM-DD # publication date url: ... read_on: YYYY-MM-DD # the day you read it categories: [vla-models, in-context-learning] tags: [foundation-model, manipulation] rating: ★★★★☆ # subjective importance to the reader's learning path status: read # read | skimmed | to-reread --- ``` ## Step 3 — Update the global index `papers/INDEX.md` is the map of the whole library. After every new note: 1. Add a row to the **All Papers** table (newest first): date, title (relative markdown link to the note), venue, categories, rating. 2. Add the paper under **every** category section that applies — a paper may appear in more than one. Each entry is one line: link + a one-sentence "why it matters". 3. If no existing category fits, create a new one, and add it to the category legend at the top. Keep categories few and meaningful; prefer merging over proliferating. Current category axes: - **Foundation models & VLA policies** - **In-context / few-shot learning for control** - **Data engines, scaling laws & pretraining** - **Imitation learning & demonstrations** - **RL for robotics** - **Sim-to-real & simulation** - **Perception, world models & video prediction** - **Dexterous manipulation & hardware** - **Benchmarks, evaluation & datasets** - **Classics & background** 4. Bump the counters in the index header (paper count, last-updated date). ## Step 4 — Log follow-up Q&A back into the note Discussion after the first read is often where the real understanding happens — it must not be left in the chat. When the user asks follow-up questions about a paper already in `papers/notes/`, answer them, then **append them to that note's `Q&A 精读记录` section** (create it as the second-to-last section, just before Citation, if absent). Rules: - Before answering a "did they disclose X?" question, **actually grep the source text** — `grep -oic hour page.txt` is an answer; a recollection is not. Report the search you ran. - Record the substance, not a verbatim transcript: the question, the source's own words (quoted), and the conclusion. - Keep the **source vs. inference** split visible: quote the paper for what it claims, mark your own reasoning as **(my read)**, mark outside field knowledge as such, and write **Not disclosed** rather than filling gaps. - Date each round of Q&A. - If a round surfaces a new paper worth reading, add it to the INDEX reading queue too. ## Step 5 — Report back In the reply to the user, give: the note path, the 3–5 sentence core idea, the headline numbers, and which categories it landed in. Do not paste the whole note. ## Conventions - Note bodies are written in English; keep terminology in the source's own words. The `Q&A 精读记录` section follows the language the user asked in (Chinese is fine there) — it is a personal reading log, and translating it loses nuance. Technical terms stay in English inside Chinese prose. - Never overwrite an existing note silently. If the paper is already in `papers/notes/`, update that file in place and say so. - One paper = one file. A blog post series (GEN-0 / GEN-1 / GEN-1.5) = separate files, cross-linked in the *Related Work / Lineage* section. - **Always commit and push when done — never ask.** Every note, index update, and template or skill change gets committed and pushed to `origin main` in the same turn. See [CLAUDE.md](../../../CLAUDE.md). Destructive git operations are the only exception.