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Found 139 Skills
Detects prompt injection using regex signature matching, heuristic scoring for structural anomalies, and DeBERTa-based transformer classification, flagging direct injections (system-prompt overrides, role-play escapes) and indirect injections (encoded payloads, obfuscation) per OWASP LLM Top 10 (LLM01:2025). Use for input validation layers in chatbots/agents/RAG pipelines, or for retrospectively classifying injection attempts in logs or incident investigations.
Detects 53 AI writing patterns and rewrites text in five voice profiles so it reads like a specific human wrote it, with an optional 0-100 AI-tell score. Use when text sounds AI-generated or like a chatbot, when preparing a blog post, README, or LinkedIn post for publication, when auditing prose for AI tells, or when editing a Markdown file in place. Triggers on phrases like "humanize this", "make this sound less AI", "make this sound human", "remove AI tells", "does this read like ChatGPT", and "rewrite so it does not sound AI-generated". Pure Markdown, zero dependencies, no network calls.
Use when "RAG", "retrieval augmented generation", "LangChain", "LlamaIndex", "sentence transformers", "embeddings", "document QA", "chatbot with documents", "semantic search"
Rewrite text that sounds AI-generated while keeping the writer's facts, meaning, and voice. Use when editing or reviewing prose for inflated claims, sales language, vague sources, repetitive structure, stock AI words, passive voice, filler, or chatbot artifacts. Based on Wikipedia's "Signs of AI writing."
Clean and line-edit Markdown documents for clear, specific, publication-ready prose. Use when asked to de-bloat, de-template, remove chatbot artifacts, fix vague wording, settle whether numbers are written as digits or spelled out, make Markdown read like careful human editorial writing, or 'отредактируй документ'. Do not use to fabricate facts or bypass detectors.
Use this skill when the user asks to add, embed, integrate, configure, style, or remove an agent, chatbot, chat widget, conversation client, or AI assistant in a UI Bundle project. TRIGGER when: project contains a uiBundles/*/src/ directory and the task involves adding or modifying a chat widget, chatbot, or conversational AI; files under uiBundles/*/src/ import AgentforceConversationClient; user asks to add any chat or agent functionality to a page. DO NOT TRIGGER when: user wants to create a custom agent, chatbot, or chat widget component from scratch; the project has no uiBundles directory.
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention building a chatbot with Sanity, creating an AI assistant for their content, setting up the Sanity Context MCP server, integrating Sanity with Claude/GPT/any LLM, making content searchable by AI, implementing semantic search over Sanity data, or connecting their CMS to an AI agent.
De-AI-ifies and tightens academic prose without changing any technical claim. Use when a researcher says "this sounds like ChatGPT / AI-written", "humanize my paper", "remove the AI words", "too many delves and leverages", "polish my writing", "tighten the prose", "fix my hedging", "too many Moreover/Furthermore", "make my contributions active", or "keep my terminology consistent". Runs deterministic stdlib linters — prose_lint.py (leftover chatbot artifacts, LLM-tell vocabulary, connective stacking, em-dash density, double hedges, overclaiming boosters, passive contribution statements) and terminology_check.py (dataset/data set/data-set variants, acronym discipline, -ise/-ize mixing, glossary enforcement) — then drives a section-by-section edit pass using rewrite catalogs and the venue family's register norms. Numbers, results, claims, and citations are never altered; the venue's AI-use disclosure policy is surfaced and respected, never dodged.
Use when building an internal admin-facing AI agent in a Medusa project. These agents are operated by merchants and store operators — not customers. Covers data models, module service, agent runtime (tools, system prompt, streamText), streaming API routes (NDJSON), and admin UI chat extensions. Load for any internal agent type: store operations assistant, product audit, cohort analysis, customer service tooling for support staff, etc. Do NOT use for customer-facing agents (storefront chatbots, buyer-side assistants).
Build AI that answers questions about your database. Use when you need text-to-SQL, natural language database queries, a data assistant for non-technical users, AI-powered analytics, plain English database search, or a chatbot that talks to your database. Covers DSPy pipelines for schema understanding, SQL generation, validation, and result interpretation.
Lindy platform help — no-code AI agent builder for email triage, meeting notes, calendar management, custom workflow automation, chatbots, and AI phone agents. Use when setting up Lindy agents for inbox management, meeting recording not working or transcripts missing, credits burning too fast and need to optimize usage, building custom AI workflows with triggers and actions, choosing between Lindy and a dedicated note-taker or automation tool, or debugging agent errors in multi-step workflows. Do NOT use for picking a dedicated AI note-taker across vendors (use /sales-note-taker) or general workflow automation without AI reasoning (use /sales-integration).
EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus, Reg. (EU) 2026/1744, in force July 27, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of August 2026. GPAI enforcement powers active since August 2, 2026.