리서치·학습 스킬

Use when a user wants an editable PowerPoint or PPTX made from a scientific or academic paper, paper PDF, DOI, PMID, arXiv link, article text, abstract with figure legends, or research notes for a journal club, group meeting, lab meeting, paper sharing, thesis seminar, or research talk; also when they ask for 论文转PPT, 文献汇报, 组会PPT, or 论文解读PPT. Not for general-purpose slide decks, business presentations, slide-image reconstruction, or paper-search-only requests.

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Convert literature reviews, paper folders, thesis drafts, journal-style reports, or research outlines into rigorous academic slide decks and review artifacts. Use when Codex must create, rebuild, or polish PPTX presentations from scholarly sources while preserving academic logic, citation-aware image/formula handling, editable layouts, figure explanations, template fidelity, and export-based visual QA.

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論文・研究ノートの主張を根拠に対応させ、編集可能な日本語の研究発表を作る。

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Generate editable learning PPTX decks by first creating HTML slides, or convert local HTML slide decks and single-page HTML presentations into editable PPTX files by rendering in a browser, reading DOM element positions, extracting inline SVG assets, and rebuilding text, shapes, gradients, bullets, and icons as separated PowerPoint objects. Use when a user asks to generate PPT/PPTX from a topic, outline, course material, study notes, or structured content, or asks for pixel-level/browser-positioned HTML-to-PPT/PPTX conversion with editable/separate elements instead of one full-slide screenshot.

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LearnDeck原典のHTML-to-PPT DOM実測converterで、日本語HTMLからnative文字と図形・個別SVG画像を持つPPTXを作る。

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Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.

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Generates ideas with named methods from creative practice (SCAMPER, lateral provocations, constraints, pataphysics, and more), routed to the user's situation. Use for open-ended generative or selective requests: "I want to make or start something", "I'm stuck", "inspire me", "make this weirder", "help me pick", or inventing a research question.

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Use when the user asks for deep or academic research — a literature review, PRISMA systematic review or meta-analysis, fact-check, evidence synthesis, APA 7 research report, or Socratic guidance to sharpen a vague research question. Runs a 13-agent pipeline with full, quick, review, lit-review, fact-check, socratic, and systematic-review modes.

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Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo

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Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity

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Runs an autonomous experiment loop on any programming task: you define the goal, metric, and eval command; the agent edits code, measures, and keeps or discards each change until interrupted. Use when optimizing a measurable target (speed, accuracy, size, score) by iteration.

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Write the document of a research run — plan the question and the outline with rs_plan, write prose and declare its claims together with rs_write, choose the claim strength the evidence actually holds, follow the section structure the run's kind maps to, read the draft back, and build a watermarked draft before the gated clean build. Use when a run's document has to be written, a section drafted, a claim bound to a source, or a build attempted.

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Get literature into a research run when the plugin fetches nothing — fetch the source yourself with web_fetch / web_search or take a file the person already has, READ it with the pdf_* tools or ocr, then ingest record and text together with rs_cite, bind locators, and cite with [@key]. Use when a run needs sources, when a library export has to come in, when a citation key is unknown, or when a claim cannot be checked against a source.

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Choose the design and the numbers a research run can honestly claim — write the structured METHOD RECORD (databases, date of access, search string, criteria, screening counts) that r0 validates, pick the claim strength a design can actually carry, record a statistic as data rather than prose, route to the reporting guideline the design owes, and decide what to preregister. Use when a run's question, design, search or statistics have to be settled before the writing, or when a claim needs a strength or a number attached to it.

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Record the statements a journal requires and a reader checks — authors with their CRediT contributions, ethics approval that names the body and the reference number, how consent was taken, funding with grant numbers, conflicts of interest, data availability with an address or a reason, and the use of generative AI — as a validated record that the submission folder prints and the manuscript never carries. Use when a run is heading for submission, when an author asks who should be listed, when consent, approval or data sharing has to be stated, or when the venue's AI policy comes up.

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Hand a research run over as a file — read `rs_open action=capabilities` for the formats this build writes, choose between `md`, `docx`, a self-contained `html`, the `ris`/`bib`/`enw` library exports and `tex`, pick `draft=watermark` while working or `draft=clean` to hand it over, and read `build/build.json` for what was built from which bytes. Use when a document is finished enough to leave the run, when a citation style or an export has to be chosen, or when a build refuses.

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Run a research project as a folder on disk — open the run root first, record the user's own instruction verbatim, open the two frame gates and stop for the human to answer them, and keep the stage the ledger says it is. Use when the user asks to start, resume or check a research run, a paper, a review, a brief, a report, a literature review or a protocol.

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Work the verification ladder of a research run with rs_verify — read the ladder report before claiming anything is checked, run the two file rungs (r1-record, r2-locate) that need no reader, record the r3-support verdicts and strength verdicts that only a reader can make, tell a miss from an inconclusive, and know what a clean build will still refuse. Use when a document is written and about to be called checked, when a claim's quote does not match its source, or when a gate or build answers with an integrity refusal.

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Work the review of a research run with rs_review — read the manuscript and record the panel's concerns with the evidence that grounds each one, keep the author's reply and the re-review's finding in their separate columns, run the devil's advocate with the concession threshold the tool enforces, and write the panel report and traceability matrix a response-to-reviewers letter is built from. Use when a document is ready for review, when a concern has to be answered or re-reviewed, or when an attack or a concession is being recorded.

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Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.

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Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.

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Standard Operating Procedures for read-only codebase exploration, symbol search, dependency mapping, code tracing, code review, architecture analysis, technical research, source evaluation, and evidence-based reporting.

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When a bug or regression is reported, the FIRST step — before fixing — is to research how and when it was introduced (git archaeology), then record that finding on the tracking issue/PR. Use the moment a bug, error, broken build, or "this used to work" is reported, before writing a fix. Produces a first-bad-commit (or "not a code regression") note you paste onto the issue.

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Drives the Phase 4-5 dev pipeline state machine with sub-agent reviews and bounded autoresearch gates. Use when running /pipeline or executing an approved plan.

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