Paper Learning

This is a Hermes-native paper-learning workflow skill.

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-package because 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 or the session ends mid-paper, continue section-by-section: record each chunk with omh paper progress and, in a new session, run omh paper list then omh paper show <paper_id> to resume from the recorded next section instead of re-reading from the abstract.
• If the paper is longer than one read_file window, call omh_document_plan (action=plan with the pages, lines, and outline the first read showed) and walk its numbered ranges, marking each covered.
• If the user asks for validation, citation checking, math proof review, or reproduction, create a separate observed-evidence or coding handoff path.

Workflow Lane

• Current lane: Research and company ops (product-docs, source-finder, web-research, research, model-optimization, inference-serving, model-finetuning, research-brief, +20 more) - research, signals, ops, and briefings.
• If intent belongs to another lane, hand back to oh-my-hermes or name the adjacent workflow.
• Shared product, routing, compatibility, and evidence rules: omh-routing/references/skill-common-rail.md.

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 Hermes role: researcher 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_summary through 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.

Handoff policy:

Keep paper explanation in Hermes. Route file export to materials-package, current-source discovery to research, recurring monitoring to research-department, and reproduction or implementation to an accepted coding handoff only after the explanation plan is accepted.

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.json and 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 to ledger.jsonl; omh paper validate checks 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

Preferred harness for this skill: paper-learning.

omh runtime record --skill paper-learning --harness paper-learning --status started

Record observed delegation results; otherwise return not_available or not_observed. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence.

• Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion. Reply in the user's own words and the host's own voice: its SOUL.md persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; 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.

Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.

Shared product, compatibility, topology, memory, harness, and execution rules: omh-routing/references/skill-common-rail.md. Load it when applicable; otherwise name an unavailable capability.