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 Robertmorrisluminousenergy177/paper-deep-reading-skill --skill paper-deep-readinggit clone --depth 1 https://github.com/Robertmorrisluminousenergy177/paper-deep-reading-skillWrote 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/robertmorrisluminousenergy177/paper-deep-reading-skill/paper-deep-reading)<a href="https://agentmods.dev/skills/robertmorrisluminousenergy177/paper-deep-reading-skill/paper-deep-reading"><img src="https://agentmods.dev/badge/skills/robertmorrisluminousenergy177/paper-deep-reading-skill/paper-deep-reading/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/robertmorrisluminousenergy177/paper-deep-reading-skill/paper-deep-reading"><img src="https://agentmods.dev/badge/skills/robertmorrisluminousenergy177/paper-deep-reading-skill/paper-deep-reading.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00113 | $0.00855 |
| Opus 5.5 | $0.00045 | $0.00342 |
| Sonnet 5.5 | $0.00023 | $0.00171 |
| Haiku 4.5 | $0.00011 | $0.00085 |
Grade A, and why
paper-deep-reading scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Deep Reading
Purpose
Turn a journal paper into a polished learning artifact: one main Obsidian Markdown note with paragraph-level translation, placed figures, detailed figure notes, beginner explanations, glossary support, a question log, and optional PDF export.
Use the PDF skill or an equivalent render-and-inspect workflow whenever the source is a PDF. For two-column journal articles, rendered pages are the source of truth for reading order and figure placement.
Default Workflow
- Inspect the source PDF: title, authors, sections, page count, figures, captions, tables, references to supplements, and any copyright-sensitive constraints.
- Create a vault-style output folder with
assets/figures/,exports/, and one main Markdown note unless the user asks for multiple notes. - Translate and explain paragraph by paragraph. Number natural paragraphs as
P01,P02, etc.; correct OCR or extraction order against page renders. - Insert each figure near the paragraph that first uses it. Store images under
assets/figures/with stable descriptive names. - For every main figure, write a figure note that explains what type of figure it is, what each panel does, what claim it supports, why it matters, and why the authors included it.
- Add beginner support at first use of key concepts, methods, axes, formulas, materials, and mechanisms. Mark claim boundaries: measured, calculated, inferred, or proposed.
- Maintain a question log for knowledge questions. Merge repeated questions into the closest existing entry instead of duplicating long explanations.
- Verify Markdown links, figure paths, section coverage, and whether the output is readable in Obsidian.
- Export to PDF only when requested. Render the note, inspect representative pages visually, and place final PDFs in
exports/.
Required References
Read only the reference files needed for the user's request:
references/reading-workflow.md: full paper-to-note workflow and quality gates.references/figure-note-guide.md: how to crop, place, and explain figures.references/beginner-explanation-guide.md: how to explain a difficult field to a novice without oversimplifying.references/obsidian-note-style.md: note structure, callouts, links, and CSS expectations.references/question-log-guide.md: how to maintain the learning question log and merge repeated concepts.
What ships with it
15 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.
- agents/openai.yaml 275 B
- assets/figure-note-template.md 293 B
- assets/note-template.md 807 B
- assets/obsidian-css-snippet.css 883 B
- assets/question-log-template.md 451 B
- references/beginner-explanation-guide.md 1.1 KB
- references/figure-note-guide.md 2.1 KB
- references/obsidian-note-style.md 1.2 KB
- references/question-log-guide.md 1.1 KB
- references/reading-workflow.md 2.0 KB
- references/v2.9.zip 478 KB
- scripts/export_obsidian_note_pdf.js 3.3 KB runs code
- scripts/extract_pdf_assets.py 1.9 KB runs code
- scripts/validate_note_structure.py 1.9 KB runs code
- scripts/validate_skill_package.py 2.5 KB runs code
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.
- 1mo ago First seen · 55 lines · 113 tokens per session scan A dcd75adc98f6
paper-deep-reading is a skill published in the GitHub repository Robertmorrisluminousenergy177/paper-deep-reading-skill (1 stars, last pushed 14d ago), licensed MIT. It adds 113 tokens to every session and 855 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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