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Humanize LLM output so it reads like a careful human wrote it. Subtracts AI-isms (sycophancy, tricolons, em-dash overuse, "delve"/"tapestry"/"testament", hedging stacks, tidy five-paragraph shapes), engineers burstiness and calibrated uncertainty, and preserves technical accuracy. Supports intensity levels: subtle, balanced (default), full, voice-match, anti-detector. Use when user says "humanize

Humanize natural-language memory files (CLAUDE.md, todos, preferences, docs) by removing AI-isms and adding burstiness while preserving every code block, URL, path, command, and heading exactly. Two modes: --deterministic (fast, regex-based, no API) and LLM (default, calls Claude for rewrite). Humanized version overwrites the original file. Plain backup saved as FILE.original.md. Trigger: /unslop-

Humanize LLM output so it reads like a careful human wrote it. Subtracts AI-isms (sycophancy, tricolons, em-dash overuse, "delve"/"tapestry"/"testament", hedging stacks, tidy five-paragraph shapes), engineers burstiness and calibrated uncertainty, and preserves technical accuracy. Supports intensity levels: subtle, balanced (default), full, voice-match, anti-detector. Use when user says "humanize

Humanize LLM output so it reads like a careful human wrote it. Subtracts AI-isms (sycophancy, tricolons, em-dash overuse, "delve"/"tapestry"/"testament", hedging stacks, tidy five-paragraph shapes), engineers burstiness and calibrated uncertainty, and preserves technical accuracy. Supports intensity levels: subtle, balanced (default), full, voice-match, anti-detector. Use when user says "humanize

Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .tldr JSON files and exports to PNG/SVG locally using @kitschpatrol/tldraw-cli.

Strip AI-slop patterns from reasoning traces (chain-of-thought, extended thinking, agent decomposition) — not final prose. Reasoning text has its own slop catalog that regular unslop doesn't target: over-explaining the question, over-hedging, over-decomposing trivial problems into 6-bullet substeps, infinite-loop rationalization. Trigger: /unslop-reasoning, "clean up my reasoning", "fix this chain

Rewrites commit messages so they sound like a careful human engineer wrote them. Strips AI/marketing slop ("comprehensive solution", "robust implementation", "leverage", "enhance", "seamlessly", "This commit..."). Keeps Conventional Commits format. Subject ≤72 chars (aim ≤50), imperative mood. Body only when "why" isn't obvious from the subject. Use when user says "humanize commit", "de-slop commi

Rewrites code review comments so they read like a human teammate wrote them. Cuts corporate-AI throat-clearing ("I noticed...", "I was wondering if perhaps...", "It might be worth considering..."). Each comment is direct: location, the issue, a concrete fix. Use when user says "humanize review", "de-slop PR comment", "make this feedback sound human", "review this PR", "code review", "/review", "/u

Analisa o comportamento de agentes Agentforce em produção usando rastreamentos de sessão e o Data Cloud. É acionado ao consultar dados de sessão STDM, registros de rastreamento do Data Cloud, investigar falhas ou problemas de desempenho de agentes, ou ao reproduzir e analisar problemas de produção.

Create and edit Remotion videos with domain-specific knowledge. TRIGGERS - Use this skill when: - User mentions "Remotion" in their request - User references a Remotion project path (remotion-videos/*, contains remotion.config.ts) - User asks to create, animate, or edit video content in a Remotion context - User wants to build compositions, animations, or video sequences in React Always invoke thi

Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to avoid context window bloat from tool definitions. Use when interacting with external MCP servers (Zapier, Sequential Thinking, GitHub, filesystem, etc.), listing available tools, or executing MCP tool calls. Triggers on requests like "connect to Zapier", "use MCP server", "list MCP too

O Agentforce Agent Script auxilia na construção, modificação, depuração e implantação de agentes. Ele é acionado quando usuários interagem com arquivos .agent, alteram o comportamento do agente, projetam ações, escrevem especificações ou testam agentes.