788 件 ・ 関連度順
概要と使いどころ
Design and run risk-targeted robustness, sensitivity, error, and baseline checks for an approved mathematical model, emitting compact machine evidence in lean mode and a final report in submission mode.
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。
Take a list of projects and their related documentation, and organize them into the SRED format for submission.
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。
When the user wants to run paid ads within directories or marketplaces. Also use when the user mentions "Taaft ads," "Shopify App Store ads," "G2 sponsored," "Capterra ads," "directory ads," "marketplace ads," "paid listing," "sponsored listing," or "directory promotion." For organic listings, use directory-submission.
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。
Senior Regulatory Affairs Manager for HealthTech and MedTech. Use for regulatory strategy, FDA 510(k)/PMA/De Novo submissions, EU MDR CE marking, global market access, and regulatory intelligence.
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。
FDA regulatory consultant for medical device companies, covering 510(k)/PMA/De Novo pathways, QSR (21 CFR 820), HIPAA, and device cybersecurity. Use for FDA submissions, predicate and substantial-equivalence analysis, and premarket strategy.
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。
Implement Terraform Provider resources and data sources using the Plugin Framework: CRUD operations, schema design, plan modifiers and validators, not-found handling, waiters for eventually consistent APIs, import support, resource design principles, and required acceptance test coverage. Use when adding or changing a resource or data source, deciding whether an API concept should be a resource, wiring a resource to the provider's configured client, handling drift or resource-not-found, or reviewing a resource implementation before submission.
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。
Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on conceded facts, wrong-forum objections, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or structured legal reasoning. Triggers on "attack this but only with points that hold", "no cheap shots", "what survives reply", "which points can I actually defend", "give me the version I can file", "double-pass adversarial review". Also use when an earlier adversarial review came back overlong or scattershot. Formal British English.
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。
RFP creation, distribution, evaluation, and shortlisting for in-house legal teams selecting outside counsel. Draft a new legal services RFP from scratch, evaluate firm responses against weighted criteria, produce a shortlist recommendation with selection rationale for GC sign-off, or design the end-to-end RFP process from scratch. Trigger on: 'draft an RFP', 'run an RFP process', 'evaluate firm responses', 'score the RFP submissions', 'which firms should we shortlist', 'selection recommendation', 'how do we run a panel RFP', 'RFP for legal services', 'pitch process', 'firm selection process', 'compare the proposals', 'we're reviewing our panel', 'panel refresh RFP', 'we need to go to market', 'request for proposal', 'evaluate the pitches', 'which firm won the RFP', 'write a legal RFP', 'RFP evaluation criteria', 'design the RFP process', 'how do we weight the criteria'.
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No Inference / Source-Locked Verification. Forces Claude to answer ONLY from user-provided materials and/or online sources actually accessed — no inference, no assumptions, no gap-filling. Every factual, legal, numerical, or procedural claim must be anchored to a cited source. Use whenever Claude reviews documents, summarises evidence, checks accuracy, drafts submissions, creates timelines, extracts facts, checks citations, analyses rules, prepares legal arguments, compares documents, verifies claims, produces chronologies, works from uploaded materials, performs legal research, checks case status, or does anything where evidential fidelity matters. Also trigger on: 'source-locked', 'no inference', 'only from the materials', 'don't assume', 'stick to the evidence', 'verify this', 'check this is right', 'work from the documents'. Overrides Claude's default tendency to fill gaps. If evidential accuracy matters, use this skill.
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。
Assesses a legal argument, submission, or piece of structured reasoning from the perspective of a judge reading it cold under time pressure. Produces a structured seven-part assessment: what the case appears to be about, immediate points of confusion, what feels strong, what feels weak, what is assumed but unproved, a provisional confidence level (low/medium/high), and what would be needed to persuade. The skill does not rewrite, improve, or attack the argument — it tells you how it actually lands on a sceptical, experienced reader with no prior context. Works on skeleton arguments, witness statements, letters before action, position statements, academic articles, and non-legal structured reasoning.
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。
Builds a high-fidelity interactive legal assessment as a single self-contained HTML artifact. Output includes a live countdown timer, contract review tasks with hover-annotated problem clauses, candidate answer textareas, model answers hidden behind reveal blocks, scenario-based legal memo tasks, strategy and function-building questions, and a pre-submission checklist that encodes the marking criteria. Use when the user needs to (1) assess a legal candidate with a realistic timed exercise, (2) train or onboard junior lawyers using problem sets rather than doctrine, (3) help a candidate prepare for a real take-home assessment they are facing, (4) build educational materials for law students, in-house teams, or compliance training, or (5) produce scenario-based training modules on specific legal topics. Triggers on "legal test", "take-home", "mock exam", "contract redline exercise", "candidate assessment", "legal training exercise", "practice test", or similar phrasing even when informal.
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Takes a skill — a .skill or .zip archive, a bare SKILL.md, a folder, or just a raw idea — and produces a package ready for public distribution on lawve.ai, plus the exact entries for the submission form. Runs a gate first: skills with no plausible legal use, unsafe code, or licensing bars are declined with reasons, and general-purpose skills that could serve legal work are offered a legal adaptation instead. Then applies the standard compliance transforms — structure, metadata, attribution, dependency ladders, orphaned-file repair, limitations disclosure — validates the result, and delivers a zip. Raw ideas are gated first, built (via skill-creator where available), then adapted. Use for "make this Lawve-compliant," "prep this skill for Lawve," "package for lawve.ai," "is this suitable for Lawve," "get my skill ready to publish," or any request to ready a skill for the Lawve catalogue.
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。
Invoice review, non-compliance flagging, rejection communication, billing trend analysis, and conversation preparation for in-house legal ops teams managing outside counsel. Review invoices against billing guidelines; flag block billing, prohibited fees, rate violations, staffing violations, late submission. Produce line-item review report and approval note. Draft rejection letter to outside counsel. Build invoice review checklist. Analyse billing trends across multiple invoices and produce a structured conversation guide for the relationship review. Identify systemic patterns and produce formal non-compliance notice. Trigger on: 'review this invoice', 'flag billing issues', 'check invoice against guidelines', 'write the rejection letter', 'build an invoice checklist', 'block billing', 'UTBMS', 'billing non-compliance', 'analyse our invoices', 'billing trends', 'prep for the billing conversation', 'relationship review', 'the firm keeps doing this', 'escalate'.
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。
Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.
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Turn drafted legal docs (privacy policy, terms) into hosted pages and set the App Store Connect Privacy Policy / Support / Marketing URLs via the ASC REST API. Use at Phase 6 / submission, after legal drafts exist. The App Privacy "nutrition label" stays manual (Apple exposes no API) — this prints the exact answers to click.
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Generate privacy policies, terms of service, and EULAs for Apple platform apps. Detects data collection patterns, third-party SDKs, and generates region-specific legal documents with Apple Privacy Nutrition Label mapping. Use when user needs legal documents or data collection disclosure for App Store submission.
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。
Senior developer-level release review for macOS/iOS apps. Identifies security, privacy, UX, and distribution issues with actionable fixes. Use when preparing an app for release, want a critical review, or before App Store submission.
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Guideline-4.3 anti-spam / originality gate — score whether an app (and each portfolio addition) is meaningfully distinct in function, content, and metadata before you invest or submit. Use at validation/new-app time and again before submission. Protects the whole developer account from 4.3 (spam/duplicate) rejections. NOT rejection-handler (that works an existing rejection) and NOT competitive-analysis (that positions in the market).
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。
TrailSnap 仓库提交、推送、需求平台与 PR 工作流规则。Use when preparing commits, pushing branches, managing the corresponding platform requirement, creating or merging pull requests, or monitoring PR CI in this repository; do not use for ordinary code changes that do not involve submission.
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。
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
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。
Review and revise academic papers with a senior-reviewer workflow. Use when an AI research/coding agent needs to work on an existing paper draft, PDF, LaTeX project, Word document, markdown manuscript, rejected paper, or paper idea that already has a concrete direction, and produce: paper maps, weakness audits, insight/novelty checks, reviewer objections, claim-experiment matrices, theory/proof checks, experiment plans, statistics/reproducibility audits, figure/table audits, ethics/compliance checks, revision plans, detailed section edits, or final submission checklists.
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。
Generate clinical trial protocols for medical devices or drugs. This skill should be used when users say "Create a clinical trial protocol", "Generate protocol for [device/drug]", "Help me design a clinical study", "Research similar trials for [intervention]", or when developing FDA submission documentation for investigational products.
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。
Khi nguoi dung muon tang traffic tu SEO, AI SEO, GEO/AEO, Google, ChatGPT, Perplexity, schema, structured data, llms.txt, programmatic SEO, local SEO, directory submissions, Product Hunt, G2/Capterra, backlinks, hoac audit website khong len top. Dung cho 'SEO audit', 'AI search visibility', 'duoc AI trich dan', 'schema markup', 'pSEO', 'local SEO', 'submit directory', 'backlink plan'. Khong dung cho setup Google Business Profile lan dau — dung skill 11-thiet-lap-kenh; khong dung cho viet noi dung bai — dung 36-content-brief.
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 the user wants SEO growth, AI SEO, GEO/AEO, Google visibility, ChatGPT or Perplexity citations, schema, structured data, llms.txt, programmatic SEO, local SEO, comparison and alternative pages, directory submissions, Product Hunt, G2/Capterra, backlinks, or a site audit. Trigger on 'SEO audit', 'AI search visibility', 'AI citations', 'schema markup', 'pSEO', 'alternative page', 'submit to directories', or 'backlink plan'. Not for first-time Google Business Profile setup, see `11-channel-setup-global`; not for writing the articles themselves, see `36-content-brief-global`.
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。