Implement commands and CVar-backed configuration with validation, authority, persistence, localized feedback, and compatibility.
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Implement commands and CVar-backed configuration with validation, authority, persistence, localized feedback, and compatibility.
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Validate UI, command, text, numeric, entity, and configuration input with localized feedback and server authority.
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Habilidade abrangente de revisão de código para TypeScript, JavaScript, Python, Swift, Kotlin, Go. Inclui análise automatizada de código, verificação de boas práticas, scanning de segurança e geração de checklist de revisão. Use ao revisar pull requests, fornecer feedback de código, identificar problemas ou garantir padrões de qualidade de código.
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Auxilia na redação de conteúdo de alta qualidade através de pesquisa, adição de citações, melhoria de ganchos, iteração em esquemas e feedback em tempo real de cada seção. Transforma seu processo de escrita de esforço solo em parceria colaborativa.
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Quando o usuário quer editar, revisar ou melhorar copy de marketing existente. Também use quando o usuário menciona 'edite este copy', 'revise meu copy', 'feedback de copy', 'revise ortografia', 'polir isto', 'melhorar isto' ou 'revisão de copy'. Esta skill fornece uma abordagem sistemática para editar copy de marketing através de múltiplas passagens focadas.
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Ajuste fino de LLMs usando reinforcement learning com TRL - SFT para ajuste de instruções, DPO para alinhamento de preferências, PPO/GRPO para otimização de recompensas e treinamento de modelo de recompensas. Use quando precisar de RLHF, alinhar modelo com preferências ou treinar a partir de feedback humano. Funciona com HuggingFace Transformers.
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Sistema autônomo multi-agente para startups em Claude Code. Ativado com "Loki Mode". Orquestra 100+ agentes especializados em engenharia, QA, DevOps, segurança, dados/ML, operações comerciais, marketing, RH e sucesso do cliente. Vai de PRD para produto totalmente implantado e gerando receita com zero intervenção humana. Inclui ferramenta Task para despacho de subagentes, revisão de código paralela com 3 revisores especializados, triagem de problemas baseada em severidade, fila de tarefas distribuída com tratamento de dead letter, implantação automática em provedores de nuvem, testes A/B, loops de feedback de clientes, resposta a incidentes, circuit breakers e auto-recuperação. Gerencia limites de taxa via checkpoints de estado distribuído e retomada automática com backoff exponencial. Requer flag --dangerously-skip-permissions.
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Use the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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Design and review client UI changes — visual token discipline, reuse-before-adding, feedback surfaces (toast vs in-place notice vs empty state), overlay and menu safety, platform window adaptation, loading states, and error copy placement. Use when adding or changing product-user-visible GUI behavior, or when reviewing such a PR.
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Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
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Review a GitHub pull request and provide structured feedback with severity ratings
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When the user wants to increase conversions on any marketing page — homepage, landing, pricing, feature, or blog; "CRO," "this page isn't converting," "low conversion rate," "bounce rate," "my landing page sucks" — or just shares a URL asking for feedback. For signup flows, see signup-flow-cro; post-signup activation, onboarding-cro; forms, form-cro; popups, popup-cro.
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Decision transparency, feedback collection, and debate invitations for AID methodology. Active in ALL phases for ALL roles.
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Use this skill when you need to review presentation materials from an audience perspective to improve their quality and effectiveness. Evaluates content clarity, visual design, logical flow, engagement factors, and Marp technical compatibility. Triggers include "review my presentation", "check my slides", "presentation feedback", or when a user has completed a draft presentation and wants comprehensive quality review.
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既存スキルへの改善要望を構造化するとき、Notion 改善要望 DB へ登録するときに使う。
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Package an AI skill, prompt workflow, or internal operating habit into a public-ready release with a catchy hook, safe redaction, useful examples, demo tasks, README copy, and launch messaging. Use when preparing a skill for GitHub, social sharing, marketplace submission, documentation, or community feedback.
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Re-evaluate auto-review findings against the original order's intent. Filters out findings that bend the intent to reduce scope. Use after Document Workflow auto-review completes (step 5→6), or when review feedback feels like it's distorting the original goal.
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Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product UI.
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Convex UI component patterns from the live Storybook preview. Use when building React components, forms, modals, navigation, feedback states, or app layouts that should match the current Convex design system. Applies to both shared primitives and dashboard style product UI.
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Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
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Simulates academic peer review, evaluating papers across Originality, Methodology, Results, and Writing to provide Major/Minor Revision recommendations with actionable feedback. Triggers when a user asks to "review my paper," "simulate peer review," or "give my paper a peer review.
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Implement a phishing report button in email clients with automated triage workflow that analyzes user-reported suspicious emails and provides feedback to reporters.
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Synthesises training survey responses and manager notes into a DRAFT training needs report by role: coded needs with record counts per role (n of N), the evidence type behind each count, anonymised quotes cited to record codes, disagreements between what staff report and what managers observe, gaps where a role is under-represented or a required skill has no evidence, and follow-up questions to settle before any course is designed. Never rates an individual, ranks a team or turns a count into a competence verdict. Use when the user asks to "analyse this training survey", "what training do our teams need", "summarise the manager feedback on skills gaps", "build a training needs analysis by role" or "which roles have the biggest skill gaps". Do not use for turning an agreed need into a course, use course-outline-builder instead; for exit interviews, use exit-interview-synthesis. Drafts for human review; never approves, authorises or signs off.
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