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Found 1,839 Skills
Manage App Store Connect code signing resources using the `asc` CLI tool. Use this skill when: (1) Managing bundle identifiers — register, list, or delete (`asc bundle-ids`) (2) Managing signing certificates — create from CSR, list, or revoke (`asc certificates`) (3) Registering or listing test devices (`asc devices`) (4) Managing provisioning profiles — create, list, or delete (`asc profiles`) (5) Setting up the full code signing chain for CI/CD pipelines (6) User says "set up signing", "create a profile", "register my device", "revoke cert", "list certificates", "create bundle id", or any code-signing related task
Generates a 6-step frontend planning document pipeline (requirements → user flows → page spec → use cases → component tree → state/API integration) into docs/en/specifications/<domain>/, with domain analysis, tech stack detection, and user review gates at each step.
This skill should be used when the user asks to "validate a DataFrame with pandera", "write a pandera schema", "use pandera DataFrameModel", "add data validation to a pipeline", or needs guidance on pandera best practices for data quality.
Data pipeline expert for ETL, Apache Spark, Airflow, dbt, and data quality
Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after idea-tournament), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing idea tournaments or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use idea-tournament).
Automated content production pipeline: hot topic aggregation from 10+ platforms (Bilibili, GitHub, Reddit, YouTube, Weibo, Zhihu, etc.), AI-powered topic scoring, multi-platform content generation (Xiaohongshu, WeChat, Twitter), draft review, and auto-publishing. Use when: user wants daily content pipeline, hot topic collection, content generation, article publishing, or content factory automation.
MUST USE for any task involving the dotenvx CLI tool — encrypting .env files, running commands with injected env vars, managing secrets across environments, and decrypting at runtime. Use this skill whenever the user mentions dotenvx, dotenv encryption, DOTENV_PRIVATE_KEY, encrypted .env files, or the dotenvx encrypt/run/set/get/decrypt/keypair commands. Also trigger when the user wants to: commit .env files safely to git, stop sharing secrets over Slack/chat, encrypt environment variables with public-key cryptography, set up multi-environment .env configs (production/staging/ci), manage secrets in a monorepo with -fk flag, migrate from python-dotenv or plain dotenv to encrypted envs, inject env vars into any process across any language (Node, Python, Ruby, Go, Rust, etc.), or configure CI/CD pipelines (GitHub Actions, Docker) with encrypted env files. This skill contains the authoritative CLI reference — without it, responses will hallucinate non-existent commands and flags.
Quick reference for pipe and flow. Use when user needs to chain functions, compose operations, or build data pipelines in fp-ts.
Builds and deploys data processing and ML training pipelines using TrueFoundry Workflows (built on Flyte). Use when creating DAGs, orchestrating multi-step tasks, scheduling ETL pipelines, or running ML training workflows.
Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
Open-source pipeline: fork, sanitize, and package private projects for safe public release. Chains 3 agents (forker, sanitizer, packager). Triggers: '/opensource', 'open source this', 'make this public', 'prepare for open source'.
Use Kotlin idioms safely in Android apps, including nullability, data classes, sealed types, extension functions, and collection pipelines.