「draft」の検索結果

One-shot conventional commit; bundled scripts adaptively gather diff context, draft the message, and stage+commit — pass `ask` to confirm first or add a hint for the title. Use only when the user asks for a commit.

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Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".

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Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Quality (side-by-side). TRIGGER when the user asks to "score this paper draft", "evaluate against the benchmark", "compare two papers", or "run the autoraters".

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EZMM writer-stage adapter for the vendored PaperOrchestra skill pack. Use by default during pipeline/04-paper-writing for outline-first paper drafting, literature-review planning, section writing, and refinement discipline. The adapter maps EZMM runtime artifacts to PaperOrchestra-style inputs, runs PaperOrchestra-first writing automatically, and returns EZMM-compatible paper.md.

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Codex-led multi-model workflow (Codex + Claude + Gemini). Use when the user asks to run `synapse <cmd> ...` to generate draft diffs/audits and persist artifacts to `./.synapse/**`.

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Review public site content for editorial quality, source support, prompt residue, duplicate blocks, translation drift, hidden filler, and human usefulness before SEO or LLM-friendly publication. Use this skill when the user asks to quality-gate news briefs, longform explainers, blog posts, topic pages, project pages, translated content, or generated article drafts without changing the live publishing pipeline.

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Designs Claude Code prompts and CC environments. Produces CLAUDE.md drafts, agent topologies, scope-authorization frameworks, halt triggers, Skills/hooks/MCP plans, chat-to-CC handoff specs, and EXECUTION_PLAN.md remediation plans. Five modes: DESIGN (new CC deployments), EVOLVE (updates from friction), RESEARCH (evaluate a CC tool/pattern), TEMPLATE (reusable artifacts), REMEDIATE (consume hygiene findings → produce + execute plan). Do NOT use REMEDIATE for direct cleanup (Cat 1–10 — use rootnode-repo-hygiene Phase 2). Do NOT use for hygiene scanning (rootnode-repo-hygiene), chat prompts (rootnode-prompt-validation), or chat Projects (rootnode-project-audit).

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Full AI-assisted workflow for long-form SEO content (2,000+ words). Covers JTBD strategy, E-E-A-T quality standards, and 5 production phases: research, outline, draft, editing, and SEO/publishing. Built for B2B marketing agency context. Use when: user wants to write or optimize an SEO article, mentions "SEO content", "blog post", "GTM article", "long-form content", or asks to create content with keyword strategy.

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Draft, expand, revise, structure, and maintain a full Islamic University of Technology BSc thesis from source documents using the local iutbscthesis LaTeX template. Use when writing or editing thesis metadata, front matter, abstract, chapters, related works, methodology, results, discussion, conclusion, citations, appendices, figures, tables, code listings, or compile guidance for main.tex. Also use when the user expects an AI agent to turn papers, notes, PDFs, LaTeX sources, bib files, data tables, and assets into a substantial thesis manuscript chapter by chapter without requiring repeated babysitting.

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Use when the deliverable is spoken words to be performed on camera or into a mic: video and podcast scripts, hooks, and CTAs for short-form (TikTok, Reels, Shorts), YouTube long-form, or podcast episodes. Triggers: "write me a reel about X", "I need a hook for my video", "script a 60-second video", "draft a podcast episode", "turn this idea into a script". For motion/timing/shot specs rather than the words, use motion-picture.

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Statically enforce a privacy/redaction boundary on an artifact tree before publication, the way an AST checker enforces a code contract. Builds a two-tier gate — a shape-based deny-list (regex over identifier shapes) plus a structure-aware tier that parses JSON/HTML/SVG/Markdown/code and asserts sensitive content cannot appear in meaningful positions — with a strict exit-code contract, label-only output that never echoes the patterns themselves, and false-positive narrowing instead of suppressions. Use when gating a public mirror, a disclosure draft, a wire-capture export, or any artifact that must pass a leak check before it ships, and when a plain line-grep is too coarse to trust.

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Trademark filing procedures covering EUIPO (EU), USPTO (US), and WIPO Madrid Protocol (international). Walks through pre-filing conflict checks, Nice classification, descriptiveness assessment, mark type decisions, filing basis strategy, office-specific e-filing procedures, Madrid Protocol extension, post- filing monitoring, and open-source trademark policy drafting. Use after running screen-trademark to confirm the mark is clear, when ready to secure trademark rights in one or more jurisdictions.

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Generates a complete, professional client onboarding package for AI consultants, AI auditors, and solopreneurs working in the AI space (AI strategy, automation, AI readiness audits, implementation, training, etc.). Use this skill whenever a user asks to onboard a new client, set up a client folder, write a welcome email, generate a discovery questionnaire, draft a service agreement, or create a project brief — especially in an AI consulting context. Also trigger when the user says things like "I have a new client", "prepare onboarding docs", "create a client package", or "set up a new project". Produces four ready-to-use deliverables: intake questionnaire, welcome email, service agreement, and project brief.

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Create a typed assignment branch and draft PR for one student. Use when the advisor has a concrete hypothesis and the student has no open `status:wip` or `status:review` assignment.

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Build the thing the user can't specify, choices surfaced. Use when the user needs something to react to before they can choose.

日本語の概要は準備中です。原文の説明を表示しています。

Use when asked to create an explainer document for a concept, diff, idea, or work recap. Drafts and verifies it in a scratch directory. Not for one-screen explanations: use explain-concept.

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Use when filing an approved task spec as a GitHub issue with a local archive and optional worktree implementer. Don't use for spec drafting without human interrogation and redaction gates.

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Plan work using Mighty (mt) by creating/updating specs and recording decisions, then spawning/structuring implementation tasks. Use when asked to plan/outline/break down a change, draft a spec (feature/rule/invariant/bug), record an ADR-style decision, or turn a fuzzy request into a structured Mighty spec tree with linked tasks.

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Prepare a reviewed Proto UI global release candidate as repository state after current project authority has chosen the exact version and stage. Use for draft Version identity, exact package metadata, notes, bill of materials, rehearsal, and publish dry-run. Publication remains a distinct privileged operation.

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Use when a consumer repo needs proposal-first backlog, Registry, and Atlas drafts from new project intent before source exists.

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Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.

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Facilitate design discussion — research context, clarify requirements, draft RFC/ADR

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Cut a versioned LoreWeave release — draft the CHANGELOG.md entry from what shipped since the last tag, confirm the SemVer bump and pre-release/release decision with the user, then tag and push to trigger the automated build + GitHub Release. Use when the user says "cut a release", "publish v...", "ship v0.1.0", "make a release", or asks what's changed since the last version.

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Before any multi-step work with a stated goal — a feature, a bugfix spanning multiple files, a QA sweep, a doc draft + iterations, a multi-day investigation — create an ATO Mission instead of doing it via bare `ato dispatch` calls. A Mission persists the goal + the verifiable success criteria, lets the coordinator tick drive the work across days, captures every event in a structured audit trail (SQLite + markdown narrative), and integrates parallel agents' work via merge strategies. Complement to `ato-warroom` (the cross-family decision before you start) and `ato-review` (the post-code-diff review). Missions is where multi-step work LIVES; war-rooms are where decisions ABOUT it get made; reviews are where the resulting commits get vetted. Fires when: the work has more than one decision point, a verifiable end state, or runs across more than one session. Use it for any ATO development that doesn't fit in a single dispatch.

日本語の概要は準備中です。原文の説明を表示しています。