Loading...
Loading...
Found 1,313 Skills
Remove AI-generated traces from text. Suitable for editing or reviewing text to make it sound more natural and human-written. Based on the comprehensive guide of "Signs of AI Writing" from Wikipedia. Detects and fixes the following patterns: exaggerated symbolism, promotional language, superficial analysis ending with -ing, vague attribution, overuse of dashes, rule of three, AI vocabulary, negative parallelism, excessive connecting phrases.
This skill should be used when a developer wants to capture learnings from a difficult session, record what Claude got wrong, save implementation gotchas, or update the steering docs with hard-won knowledge — for example "let's reflect", "capture what we learned", "that was painful, save this", "update the steering docs with what went wrong", "I need to debrief", "what went wrong today", "log this lesson", "save this gotcha", "document this mistake", "I want to write this down before I forget", "add this to the steering docs", or when prompted by the intervention tracker after multiple corrections. Routes each learning into the right steering doc (TECH, QA, DESIGN, or VISION) under a "Hard-Won Lessons" section.
[Pragmatic DDD Architecture] How to structure **Use Cases** using DDD and Railway-Oriented Programming (neverthrow Result types). Tailored for TypeScript + drizzle-orm + node-postgres stack. **Use whenever creating or modifying any Use Case class — even simple ones like "Exists" or "List" operations — to ensure type-safe error unions, proper transactional boundaries, Value Object-only contracts, auth-first patterns, and Result-based error handling.** Includes references to working examples (Create, List, Exists patterns). Depends on 'repositories' skill.
Identifies silent failures, inadequate error handling, and inappropriate fallback behavior in code. Zero tolerance for errors that occur without proper logging and user feedback. Triggers: When reviewing error handling, checking for silent failures, analyzing catch blocks. Examples: - "Review the error handling" -> audits all error handling in recent changes - "Check for silent failures" -> hunts for swallowed errors and empty catch blocks - "Analyze catch blocks in this PR" -> reviews every try-catch for adequacy - "Are there any hidden failures?" -> finds errors that get silently ignored
Workflow for learning CuTe Python DSL by reading, importing, profiling, and extracting reusable patterns from CUTLASS Blackwell example kernels. Use when: (1) studying CUTLASS CuTe DSL reference implementations, (2) importing CUTLASS examples into the project runtime infrastructure, (3) building CuTe DSL knowledge base entries from profiling experiments, (4) understanding CuTe DSL API patterns, TMA pipelining, warpgroup scheduling, or persistent kernel structure.
Verint Open Platform help — enterprise CX automation with Da Vinci AI bots (Quality Bot 100% QA, Coaching Bot real-time guidance, Wrap Up Bot auto-summaries, CX/EX Scoring, TimeFlex agent scheduling, Exact Transcription 80+ languages), WFM forecasting/scheduling/adherence, knowledge automation, IVA virtual assistants, speech/text analytics, financial compliance, Verint Marketplace 350+ listings. Use when Verint reports loading slowly or showing inconsistent data, Quality Bot not scoring interactions correctly, Coaching Bot recommendations irrelevant, WFM forecasts off vs actual volume, Verint API integration or developer portal questions, comparing Verint vs NICE vs Genesys WEM capabilities, or connecting Verint to your CCaaS or CRM. Do NOT use for choosing between CCaaS platforms (use /sales-ccaas-selection) or for QA tool comparison across vendors (use /sales-coaching).
Use this skill when the user asks to call an authenticated HTTP API (for example "call the GitHub/OpenAI/Slack API", "hit an endpoint that needs a bearer token") and the `sesame` CLI is already installed on this device. The agent invokes `sesame request`, which forwards the HTTP call through the user's own broker and attaches the auth header server-side. The skill does not install software, does not read credentials from the environment, and runs shell only within the fixed `sesame` subcommand surface (`request`, `status`, `hostnames`, `login`, `refresh`). Skip for unauthenticated public endpoints, localhost services, or when the user has already exported a token in the environment for direct use.
Build explicit learn/do-not-copy contracts for image and video generation references. Use this when a prompt uses benchmark videos, contact sheets, frames, or product images and you need to state exactly what the model should learn, what identity elements must change, and which references should be excluded from the first test.
Check and resize images for social media platforms. Run scripts/check.js to validate any image against specs for Instagram, Facebook, X (Twitter), LinkedIn, TikTok, YouTube, Pinterest, Snapchat, and Threads — get a ranked match list with exact resize commands. Run scripts/resize.js to export a correctly-sized copy. Use when a user asks to validate image dimensions, resize an image for a platform, check if an image fits a spec, or prep assets for social media posting or ads.
Learn how to implement the Syncfusion Angular Carousel component for displaying slides with images and content. This comprehensive skill includes complete API documentation with all 30 properties, 5 methods, 2 events, and working code examples. Use when creating image galleries, product showcases, featured content sliders, news rotators, or implementing carousel navigation with animations.
Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).