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Remove telltale AI-writing patterns from README, docs, and user-facing text. Must be done line-by-line, manually. No regex. Use after agents write any user-visible prose.

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。

Run a regelrecht branch locally end-to-end (worktree + Docker stack + DB), with the workarounds needed when developing inside the dev container against Docker Desktop. Accepts a branch name or a PR number. Subcommands: bare arg = start, `stop <arg>` = shut down, `clean <arg>` = shut down and remove worktree.

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。

Identify and remove phrasing, structure, and word choices that signal AI authorship. Runs iterative passes through fresh voice-agent instances with the orchestrator acting as gatekeeper on every change. Use on a cover letter before submission, or on any prose that has to read as human-written.

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。

Detect and rewrite AI writing patterns to make content sound authentically human. Supports voice calibration from the author's own writing samples. Use when asked to humanize text, remove AI patterns, calibrate voice, audit content for AI detectability, or check if writing sounds like ChatGPT. Triggers: /humanize, /voice-calibrate, /audit-ai

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 jargon and restore human voice to text

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How to write source comments, doc comments, and test names/tags that have lasting value — and what to never write. Consult before adding or editing comments in core/**, examples/**, tools/**, test/**, docs/**, or any shipped source. Handles "write a comment", "is this comment ok", "comment hygiene", and keeping new code from adding the breadcrumbs the cleanup stream removes.

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。

Search, inspect, plan, apply, remove, pack, and scaffold local Pulp package manifests. Use for Pulp-native source/UI/template kits and for untrusted or semi-trusted manifest-bearing artifacts that must be reviewed before project mutation.

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。

Validate, install, update, list, rescan, remove, and reveal data-only Pulp content packs for installed plugins. Use for presets, themes, samples, sample banks, wavetables, and other end-user data that must be reviewed before install or update.

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。

Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.

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。

Deletes merged git branches (local and remote) and flags stale unmerged branches for manual review. Use when user mentions "cleanup branches", "delete merged branches", "prune old branches", "remove stale branches", "branch cleanup", or runs /cleanup-branches command.

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。

Sync the yaah marketing website (website/index.html) with the current project state — features, CLI commands, skills, agents, hooks, and installation instructions. Use this skill whenever the user adds, removes, or changes a feature, CLI command, hook, skill, agent, MCP server, or LSP provider AND the website should reflect that change. Also use when the user explicitly asks to update, sync, or refresh the website, or says things like 'update the site', 'keep the website current', 'reflect this on the website', or 'the website is out of date'.

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。

Create and edit Canva designs, generate images, remove backgrounds, recover editable layers, and work with Canva libraries. Use for branded presentations and slide decks, campaign artwork, flyers and banners, applying saved brand kits and templates, and resizing designs for social posts and stories through Canva's official MCP server.

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。

Run a focused tech debt reduction sprint — inventories all technical debt (TODOs, outdated deps, missing tests, god objects), fixes code smells, removes dead code, then hardens with a review pass. Use when a codebase feels sluggish, before a major feature push, or on a regular maintenance cadence.

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。

Deep codebase cleanup — kills dead code, fixes all lint/format warnings, removes orphaned files, cleans stale TODOs, strips security hazards, tightens TypeScript strict mode, and organizes imports. Triggers: clean up, dead code, unused imports, lint, technical debt cleanup.

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。

Multi-pass editor that removes AI-writing tells from drafted content — eliminates filler phrases, balances sentence length, restores opinion and voice, and strips em-dash overuse so posts sound human and opinionated rather than ChatGPT-generic..

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。

Transform reference photographs and visually dense images into sparse, recognizable, high-saturation flat-vector-style illustrations through semantic compression rather than literal tracing. Use when the user asks for photo-to-flat illustration, photo-to-vector-style redraw, 照片转扁平插画, 无渐变高饱和插画, iconification, visual simplification, composition-preserving abstraction, a consistent minimal illustration set, or revisions that remove gradients, glow, texture, blur, clutter, text, logos, numbers, or UI. Default to human-perceived semantic complexity 6 out of 10 or lower, fixed-HSB solid fills, crisp boundaries, and no gradients or light-halo effects.

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。

把原始口播剪干净并配上字幕。Use when the user asks to clean up, rough-cut, or subtitle a talking-head (口播) video: remove long pauses, filler sounds, stutters, retakes and slips, then add subtitles.

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。

Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).

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Use when executing admin-level cleanup in a Salesforce org: deleting unused fields, removing inactive Flow versions, deactivating legacy automation, running Salesforce Optimizer or Org Check, and performing destructive metadata deploys. Triggers: 'clean up unused fields', 'delete inactive flows', 'run Optimizer', 'org has too many custom fields', 'remove old workflow rules', 'Flow version limit'. NOT for assessing or reporting on technical debt (use architect/technical-debt-assessment). NOT for code-level refactoring or Apex cleanup (use apex/ skills).

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。

Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in HyperFrames HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For dev-loop CLI commands (init, lint, inspect, preview, render) see the hyperframes-cli skill; for asset preprocessing commands (tts, transcribe, remove-background) see the hyperframes-media 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。

Use this skill when debugging runtime behavior requires live data from the running app, temporary instrumentation, or hypothesis verification through logs. Trigger for async timeouts, stale or incorrect state updates, race conditions, event ordering bugs, intermittent failures, browser/client behavior that static inspection cannot explain, or any issue where the agent should create a local debug HTTP server, insert temporary probes, ask the user to reproduce, inspect .debug/debug.log, then remove all debug instrumentation and assets.

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 text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.

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。

Detects tests that validate framework/library behavior (Prisma, Express, bcrypt, JWT, axios, React hooks) instead of OUR code. Returns findings with REMOVE decisions.

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 features, fixing bugs, or refactoring code that may invalidate existing docs. Detects stale documentation by matching the code diff against in-repo doc files and applies targeted updates. Relevant when code changes rename, remove, or add APIs, fields, config keys, or CLI flags. Also applies when the user says "update docs", "check docs", or "are the docs stale", or when reviewing a branch for documentation accuracy.

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。