Paper Learning
SkillDocs & knowledgeLets your agent explain this paper or paper PDF section by section at a chosen detail level.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Paper Learning skill
About this skill
[omh] Paper or paper PDF to understand: explain a supplied paper or paper/PDF at a selected level while preserving full section coverage and source evidence boundaries. Use when the user says: paper-learning, paper learning, paper-explainer, paper explainer, paper explanation, explain this paper, ex
What this skill tells your AI
The instructions your AI receives, as published by rlaope/oh-my-hermes in agent-skills/omh-paper-learning/SKILL.md and read by ahel’s review.
This is an OMH paper-learning workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
paper-learning exists so Hermes can act like a strong human tutor for papers: choose the right explanation level, walk through the full paper section by section, and keep PDF extraction and validation evidence honest.
Do Not Use When
- The request asks to export, convert, render, or package a file; use
materials-package. - The request asks for daily/weekly paper monitoring, digest, source inbox, or Scout/Analyst/Briefer operations; use
research-department. - The request asks to find current papers or sources when no supplied paper exists; use
research. - The request asks for a visual/image card; use
img-summary. - The request asks to implement or reproduce the paper's code; prepare a coding handoff only after a paper learning or reproduction plan is accepted.
Examples
Good example:
- Prompt: paper-learning 이 논문 PDF를 아주 쉽게 설명해줘. 내용은 줄이지 말고 섹션별로.
- Expected behavior: Prepare paper_learning_card/v1, ask or record level=very_easy, mark PDF extraction/source_state evidence, then explain section-by-section with a coverage ledger.
- Why: The user supplied a paper/PDF explanation intent with an explicit level and coverage-preserving constraint.
Bad example:
- Prompt: paper-learning 이 PDF를 PPT로 변환해서 공유용 파일 만들어줘.
- Expected behavior: Route to
materials-packagebecause the user wants file conversion/export, not conceptual paper explanation. - Why: PDF file output and render QA are material packaging work, not paper learning evidence.
Completion Checklist
- The selected explanation level is one of: very_easy, moderate, expert, choose.
- The source_state is recorded and scoped to observed text or extraction evidence.
- The coverage ledger lists observed, missing, or prepared sections before claiming completion.
- The explanation is section-aware and does not compress away claims, equations, figures, limitations, or reproducibility notes.
- Not-observed boundaries remain visible: full_pdf_extraction, figure_ocr, external_citation_check, math_proof_validation, code_or_benchmark_reproduction, peer_review_or_claim_correctness.
Recovery Notes
- If no paper text is observed, prepare the learning card from metadata only and ask for an attachment, excerpt, or extraction evidence.
- If only an abstract or excerpt is supplied, label the result as excerpt explanation and list missing sections.
- If context is too long, continue section-by-section and keep covered / next / missing state in the ledger.
- If the paper is longer than one read window, plan numbered page or line ranges in a durable host-owned ledger before reading, walk them in order, and mark each covered; the native OMH plan tool is unavailable in this projection.
- If the user asks for validation, citation checking, math proof review, or reproduction, create a separate observed-evidence or coding handoff path.
Use When
Use when Hermes should explain a supplied paper, arXiv entry, paper PDF, pasted excerpt, or extracted paper text at a selected level while keeping a coverage ledger instead of shrinking the paper into a lossy summary.
Strong routing signals: `paper-learning`, `paper learning`, `paper-explainer`, `paper explainer`, `paper explanation`, `explain this paper`, `explain this arxiv paper`, `paper walkthrough`, `research paper explanation`, `arxiv paper explain`, `pdf paper explain`, `paper pdf explanation`, `explain the attached paper`, `explain this pdf paper`, `without dropping details`, `very easy paper explanation`, `moderate paper explanation`, `expert paper explanation`, `논문 설명`, `논문 해설`, `논문 쉽게 설명`, `논문 아주 쉽게`, `논문 적당한 난이도`, `논문 전문가급`, `이 논문 설명해줘`, `이 논문 PDF 설명해줘`, `논문 PDF 쉽게 설명`, `논문 내용 줄이지 말고`
Catalog Metadata
Category: research
Phase: paper-learning
Quality tier: paper-learning-gated
Reasoning demand: standard
Quality bar:
- Ask for or state the explanation level before drafting: very easy, moderate, or expert.
- Record source_state as one of: metadata_only, excerpt_text_observed, file_text_extraction_observed, full_text_observed, unknown_or_missing.
- Preserve the coverage policy
coverage_preserving_not_lossy_summarythrough a section-by-section ledger. - Explain by chunks when the source is long; keep each chunk linked to coverage_ledger status.
- List missing sections and not-observed claims before presenting the explanation as complete.
Required inputs:
- paper identity or attachment reference
- observed text scope or extraction evidence
- explanation level: very_easy, moderate, expert, or choose
- coverage scope: full paper, selected sections, or supplied excerpt
- output language when different from the source
Expected outputs:
- paper_learning_card/v1
- explanation level metadata
- source_state boundary
- coverage ledger
- section-by-section explanation outline
- missing-section and not-observed list
Artifact expectations:
- record the card with
omh paper plan --title <title> --source <path or url> --level <level> --source-state <state>, which writes paper_learning_card/v1 to$OMH_HOME/paper-learning/<paper_id>/card.jsonand hashes a local source file without parsing it - record each explained chunk with
omh paper progress <paper_id> --covered <section> --next <section> [--missing <section>] [--note <text>], which updates the coverage ledger and appends one line toledger.jsonl;omh paper validatechecks the store
Safety rules:
- Do not claim full PDF extraction, figure OCR, external citation checking, math validation, code reproduction, peer review, or full-paper coverage without observed evidence.
- A pasted abstract or excerpt supports only excerpt explanation until the remaining sections are observed.
- Level changes may change scaffolding, vocabulary, analogies, and critique depth, but must not drop substantive content.
- End each chunk with covered / next / missing rather than done unless the coverage ledger is complete.
Runtime Evidence
Use the current host's own tools and subagent/task mechanism when available;
otherwise run the same lanes sequentially or name the unavailable capability.
A prepared plan, handoff, checklist, or skill installation is not execution,
review, CI, merge-readiness, or merge evidence. Record actual tool results, or
not_observed / not_available, in the record; never invent dispatch or host
accounting.
Treat supplied context as advisory, not proof of hidden memory reads or writes.
State scope, constraints, verification, and the stop condition before work.
Reply in the user's own words and the host's own voice: OMH's record terms
(surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in
records and tool calls, never in the sentence the user reads unless they ask
about one; and when a stop condition or a decision the user owns ends the turn,
offer the next action as a question rather than declaring what will not be done.
Supporting paths are relative to this skill directory; sibling skill paths are
relative to its parent. Resolve them from the host-provided skill base directory
({baseDir} on hosts that provide it), never a hardcoded install location.
A named workflow not installed here is unavailable, not permission to emulate
its host-specific capabilities. Verify through the real surface before done.
Signals
- GitHub stars
- 3k
- Forks
- 235
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
omh-paper-learning- Source
- github.com/rlaope/oh-my-hermes