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PythonReactSEOPDF
OpenClaw

paper-digest

Given an arXiv ID or URL, fetch the paper, spawn sub-agents to read its key citations, and write an executive summary under.

damoonsh0 installations selon la source☆ 0 Étoiles du dépôtv0.0.1

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install damoonsh/paper-digest

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

Paper Digest

Input

  • arxiv_id: bare ID like 2305.11206 or full https://arxiv.org/abs/2305.11206 (Normalise: strip the URL prefix, extract bare ID.)

Step 1 — Fetch the main paper

Try HTML first: web.fetch https://arxiv.org/html/<arxiv_id>

  • If HTTP 200 → use this as paper_text.
  • If Falis: add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1
  • else if all fails skip and ABORT!

If the paper_text is retrieved then write the summary to ~/.openclaw/workspace/papers/<arxiv-id>.md.

Step 2 — Extract citations

Note: DO NOT DO THIS STEP INSIDE sub-agents

Within the main agent and from paper_text, identify at most 5 citations the paper most directly builds on. Prioritize:

  • Papers that are explicitly extended or improved upon
  • Papers used as the primary baseline for comparison
  • Papers that provide the core architecture this work adopts
  • Papers referred to repeatedly (not just mentioned once) or that provide essential context

For each citation, extract either the arXiv ID or the title. Then resolve to an arXiv URL:

  • If an arXiv ID is in the reference → https://arxiv.org/html/<id>
  • Otherwise search https://arxiv.org/search/?query=<title>&searchtype=all and take the first match.

Step 3 — Spawn sub-agents for citations

Note: Ensure that the sub-agent related task is precise and concise so the sub-agent does not have to re-read the previously read SKILLs and files.

For each resolved citation:

  • Check if the file for citation exists: ~/.openclaw/workspace/papers/<arxiv-id>.md, if it does then skip and consider the sub-agent concluded.
  • If the previous step fails then spawn a sub-agent with this EXACT instruction in VERBATIM:
    • Fetch https://arxiv.org/html/<citation_id> (or add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1). If unavailable, SKIP. If retrieved then Write the summary to ~/.openclaw/workspace/papers/<arxiv-id>.md.

Step...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/damoonsh/paper-digest
Version
0.0.1
Commit
199bacee08a986059d611ecbc6ec0769d9cb3333
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# Paper Digest

## Input

- `arxiv_id`: bare ID like `2305.11206` or full `https://arxiv.org/abs/2305.11206` (Normalise: strip the URL prefix, extract bare ID.)

## Step 1 — Fetch the main paper

Try HTML first: web.fetch https://arxiv.org/html/<arxiv_id>
- If HTTP 200 → use this as `paper_text`.
- If Falis: add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1
- else if all fails skip and ABORT!

If the `paper_text` is retrieved then write the summary to `~/.openclaw/workspace/papers/<arxiv-id>.md`.

## Step 2 — Extract citations

Note: DO NOT DO THIS STEP INSIDE sub-agents

Within the `main agent` and from `paper_text`, identify **at most 5 citations** the paper most directly builds on. Prioritize:
- Papers that are **explicitly extended** or improved upon
- Papers used as the **primary baseline** for comparison
- Papers that **provide the core architecture** this work adopts
- Papers **referred to repeatedly** (not just mentioned once) or that provide essential context

For each citation, extract either the `arXiv ID` or the **title**. Then resolve to an arXiv URL:
- If an arXiv ID is in the reference → `https://arxiv.org/html/<id>`
- Otherwise search `https://arxiv.org/search/?query=<title>&searchtype=all` and take the first match.

## Step 3 — Spawn sub-agents for citations

***Note***: Ensure that the sub-agent related task is precise and concise so the sub-agent does not have to re-read the previously read SKILLs and files.

For each resolved citation:
- Check if the file for citation exists: `~/.openclaw/workspace/papers/<arxiv-id>.md`, if it does then skip and consider the sub-agent concluded.
- If the previous step fails then spawn a sub-agent with this EXACT instruction in VERBATIM: 
  - Fetch https://arxiv.org/html/<citation_id> (or add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1). If unavailable, SKIP. If retrieved then Write the summary to `~/.openclaw/workspace/papers/<arxiv-id>.md`.


## Step...

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