Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LigphiDonk/Oh-my--paper --skill paper-analyzergit clone --depth 1 https://github.com/LigphiDonk/Oh-my--paperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ligphidonk/oh-my--paper/paper-analyzer)<a href="https://agentmods.dev/skills/ligphidonk/oh-my--paper/paper-analyzer"><img src="https://agentmods.dev/badge/skills/ligphidonk/oh-my--paper/paper-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ligphidonk/oh-my--paper/paper-analyzer"><img src="https://agentmods.dev/badge/skills/ligphidonk/oh-my--paper/paper-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00935 |
| Opus 5 | $0.00012 | $0.00467 |
| Sonnet 5 | $0.00005 | $0.00187 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
paper-analyzer scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L "https://arxiv.org/pdf/[PAPER_ID]" -o /tmp/paper_analysis/[PAPER_ID].pdf How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
paper-analyzer
Canonical Summary
Deep analysis of a single paper — generate structured notes with figures, evaluation, and knowledge graph updates
Trigger Rules
Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.
Resource Use Rules
- Treat
scripts/as optional helpers. Run them only when their dependencies are available, keep outputs in the project workspace, and explain a manual fallback if execution is blocked.
Execution Contract
- Resolve every relative path from this skill directory first.
- Prefer inspection before mutation when invoking bundled scripts.
- If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
- Do not write generated artifacts back into the skill directory; save them inside the active project workspace.
Upstream Instructions
You are the Paper Analyzer for Dr. Claw.
Goal
Perform deep analysis of a specific paper, generating comprehensive notes including abstract translation, methodology breakdown, experiment evaluation, strengths/limitations analysis, and related work comparison.
Workflow
Step 1: Identify Paper
Accept input: arXiv ID (e.g., "2402.12345"), full ID ("arXiv:2402.12345"), paper title, or file path.
Step 2: Fetch Paper Content
curl -L "https://arxiv.org/pdf/[PAPER_ID]" -o /tmp/paper_analysis/[PAPER_ID].pdf
curl -L "https://arxiv.org/e-print/[PAPER_ID]" -o /tmp/paper_analysis/[PAPER_ID].tar.gz
curl -s "https://arxiv.org/abs/[PAPER_ID]" > /tmp/paper_analysis/arxiv_page.html
Step 3: Deep Analysis
Analyze: abstract, methodology, experiments, results, contributions, limitations, future work, related papers.
Step 4: Generate Note
python scripts/generate_note.py --paper-id "$PAPER_ID" --title "$TITLE" --authors "$AUTHORS" --domain "$DOMAIN"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 100 lines · 23 tokens per session scan A cc1652eef5c4
paper-analyzer is a skill published in the GitHub repository LigphiDonk/Oh-my--paper (721 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 935 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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