2,437 件 ・ 関連度順
概要と使いどころ
Use when the user asks to rewrite, humanize, clean up, or remove AI-isms from text while preserving the writer's voice, facts, intent, structure, register, and protected material.
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。
Remove AI tells from LinkedIn posts/comments: 2026 vocabulary density, reveal bridges, staccato fragments, stacked triads, performed sincerity. Tiered rewriter plus `--mode audit` LinkedIn post auditor and `--mode profile` voice builder. Not for drafting from scratch (use linkedin-post-writer) or beating AI detectors. Keywords: humanize, de-AI, post audit, post auditor, audit before posting.
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。
Repurpose existing content into a native LinkedIn post. Take a tweet, thread, YouTube video, blog, or newsletter and rebuild it for LinkedIn: re-hook before the fold, expand to the 900 to 1300 char sweet spot, add whitespace and a CTA, move links to the first comment, run the humanizer, publish via Publora on approval. Not for writing from scratch (use linkedin-post-writer), not for auditing a draft (use linkedin-humanizer --mode audit).
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。
Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.
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。
Step-by-step migration guides for moving to Playwright from Cypress or Selenium/WebDriver — command mappings, architecture changes, and incremental adoption strategies.
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。
React Three Fiber animation - useFrame, useAnimations, spring physics, keyframes. Use when animating objects, playing GLTF animations, creating procedural motion, or implementing physics-based movement.
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。
Analyze a blockchain transaction by its hash using TRES Finance MCP and generate a visual flow diagram showing all asset movements, followed by a plain-language explanation of what happened. Use this skill whenever the user provides a transaction hash and asks to "analyze", "explain", "visualize", "diagram", "show me what happened in", or "tell the story of" a transaction. Also trigger when the user pastes a tx hash (long hex string starting with 0x) and asks anything about it. Always use this skill for transaction hash analysis — do not attempt to answer from memory alone.
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。
Humanization Pipeline Orchestrator v3.1 - Multi-pass 4-layer transformation pipeline Orchestrates G5 (Auditor), G6 (Humanizer), F5 (Verifier) in sequential passes Enforces checkpoints between every pass with mandatory AskUserQuestion Supports conservative (L1-2), balanced (L1-3), balanced-fast (L1-3 merged), aggressive (L1-4) modes Rich Checkpoint v2.0: section-level scores, selective humanization, target auto-stop G5+F5 parallel execution, section-selective humanization Triggers: humanize, humanize my draft, humanize manuscript, make natural, remove AI patterns Korean triggers: 휴먼화, 자연스럽게, AI 패턴 제거
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。
Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page.
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。
Safely remove intermediate files from completed research sessions while preserving important data
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。
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact. Since 2026-08 it also carries a provenance layer (去水印): deterministic, CJK-safe cleaning of invisible-character carriers and file metadata (docx / png / jpg / svg / pdf, incl. C2PA), an honest account of Claude's statistical text watermark, and an author "ownership pass" — it never claims a text is watermark-free.
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。
Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.
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。
Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature.
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。
Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments. Platform: Google and Meta.
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 implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model/provider SDKs, fast-moving product behavior, user requests for latest/current/official behavior, unfamiliar repo docs/specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces Codex to web-search for current official docs and read primary docs before assuming from memory.
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。
Remove AI-generated code slop and clean up code style
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。
Move incoming issues and pull requests through triage states until each is actionable or closed — use when the queue has piled up or a report arrives unsorted
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。
Coordinate project or repository renames and moves involving Git, BB, services, or multiple machines. Preserve work and history while updating operational paths. Excludes ordinary file, code-symbol, and thread-title renames.
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。
Taking a multi-PR feature from "shape unknown" to merged without five review rounds per PR: spike until interfaces stop moving, write the contract, cut PRs along contract seams, one review per PR. Use when starting a feature that touches more than one lifecycle object or public interface, when a PR review keeps changing interfaces, or when splitting a large branch.
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 this skill when the docs-impact-classifier returns a structural verdict, signalling that the documentation TOC must change to accommodate the PR. Proposes TOC deltas (new pages, moves, merges) and emits new-page outline stubs that the doc-sync panel later fleshes out. Holds the 3-promise narrative (consume / produce / govern) and the persona ramps as hard constraints.
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。
Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.
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。
Keep code, tests, documentation, configuration, and other changes as tight, clear, performant, and minimal as possible without weakening behavior. Use during implementation to prevent unnecessary complexity, after behavior is proven to consolidate working changes, before handoff for a full branch audit, and when asked to simplify, tighten, clean up, reduce verbosity, remove complexity, or minimize existing work.
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。
Query and operate connected Google Search Console properties through NotFair MCP. Use for live GSC query or page performance, clicks, impressions, CTR, position, traffic changes, indexing status, URL inspection, sitemap reads or approved sitemap submission/removal, and Search Console MCP setup. Route full-site SEO audits to seo-analysis.
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。
Audit, design, write, materially revise, or remove Tutti tests. Use whenever Codex changes or reviews unit, component, conformance, integration, regression, platform, or repository tests; enforce a protected product contract, credible failure, correct owning boundary, negative-control evidence, overlap review, deterministic setup, and an executing CI lane.
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。