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Found 264 Skills
Repository packaging for AI/LLM analysis. Capabilities: pack repos into single files, generate AI-friendly context, codebase snapshots, security audit prep, filter/exclude patterns, token counting, multiple output formats. Actions: pack, generate, export, analyze repositories for LLMs. Keywords: Repomix, repository packaging, LLM context, AI analysis, codebase snapshot, Claude context, ChatGPT context, Gemini context, code packaging, token count, file filtering, security audit, third-party library analysis, context window, single file output. Use when: packaging codebases for AI, generating LLM context, creating codebase snapshots, analyzing third-party libraries, preparing security audits, feeding repos to Claude/ChatGPT/Gemini.
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.
Manage MCP servers - discover, analyze, execute tools/prompts/resources. Use for MCP integrations, capability discovery, tool filtering, programmatic execution, or encountering context bloat, server configuration, tool execution errors.
Build recommendation systems with collaborative filtering, matrix factorization, hybrid approaches. Use for product recommendations, personalization, or encountering cold start, sparsity, quality evaluation issues.
Write SQL, TypeScript, and dynamic table transforms for Goldsky Turbo pipelines. Use this skill for: decoding EVM event logs with _gs_log_decode (requires ABI) or transaction inputs with _gs_tx_decode, filtering and casting blockchain data in SQL, combining multiple decoded event types into one table with UNION ALL, writing TypeScript/WASM transforms using the invoke(data) function signature, setting up dynamic lookup tables to filter transfers by a wallet list you update at runtime (dynamic_table_check), chaining SQL and TypeScript steps together, or debugging null values in decoded fields. For full pipeline YAML structure, use /turbo-pipelines instead. For building an entire pipeline end-to-end, use /turbo-builder instead.
OpenTelemetry Transformation Language (OTTL) expert. Use when writing or debugging OTTL expressions for any OpenTelemetry Collector component that supports OTTL (processors, connectors, receivers, exporters). Triggers on tasks involving telemetry transformation, filtering, attribute manipulation, data redaction, sampling policies, routing, or Collector configuration. Covers syntax, contexts, functions, error handling, and performance.
YAML querying, filtering, and transformation with yq command-line tool. Use when working with YAML files, parsing YAML configuration, modifying Kubernetes manifests, GitHub Actions workflows, or transforming YAML structures.
Manage power and performance metrics and diagnostic logs using the `asc` CLI tool. Use this skill when: (1) Listing performance metrics for an app: "asc perf-metrics list --app-id <id>" (2) Listing performance metrics for a build: "asc perf-metrics list --build-id <id>" (3) Filtering metrics by type: "asc perf-metrics list --app-id <id> --metric-type LAUNCH" (4) Listing diagnostic signatures for a build: "asc diagnostics list --build-id <id>" (5) Filtering diagnostics: "asc diagnostics list --build-id <id> --diagnostic-type HANGS" (6) Viewing diagnostic logs: "asc diagnostic-logs list --signature-id <id>" Also trigger when the user mentions: performance metrics, launch time, hang rate, disk writes, memory usage, battery life, termination, animation hitches, diagnostic signatures, call stacks, power metrics, app performance monitoring, "why is my app slow", "check hangs", "check launch time"
Manage App Store Connect team members and user invitations using the `asc` CLI tool. Use this skill when: (1) Listing team members with their roles (`asc users list`) (2) Filtering members by role (`asc users list --role DEVELOPER`) (3) Updating or replacing a member's roles (asc users update --user-id ID --role ADMIN) (4) Revoking or removing access for a departing employee (asc users remove --user-id ID) (5) Listing pending invitations (asc user-invitations list) (6) Inviting a new team member by email (asc user-invitations invite) (7) Cancelling a pending invitation (asc user-invitations cancel) (8) User says "revoke access", "remove team member", "offboard user", "invite developer", "add someone to App Store Connect", "manage team roles", "who has admin access", "grant access", "onboard", or any team/user management task in App Store Connect
Run DuckDuckGo web searches from the terminal using `ddgr` with JSON output. Use when the task calls for lightweight web search, quick result triage, or filtering by region/time/site.