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Found 668 Skills
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for IPA runtime analysis, Frida hooks, Objective-C or Swift method tracing, Keychain inspection, SSL pinning bypass, URL scheme handling, and iOS request-signing recovery. Use when the user asks to hook an IPA, trace Objective-C or Swift runtime behavior, inspect Keychain or plist state, bypass pinning, analyze deeplinks or universal links, or replay accepted iOS requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Deno integration. Manage data, records, and automate workflows. Use when the user wants to interact with Deno data.
Apply when connecting React components to Store Framework blocks and render-runtime behavior in VTEX IO. Covers interfaces.json, block registration, block composition, and how storefront components become configurable theme blocks. Use for block mapping, theme integration, or reviewing whether a React component is correctly exposed to Store Framework.
Explains how the Tauri runtime authority enforces security policies during application execution, covering ACL-based access control, capability resolution at runtime, scope injection, and command validation for secure IPC.
Use when working with Bun's runtime APIs including file I/O, HTTP servers, and native APIs. Covers modern JavaScript/TypeScript execution in Bun's fast runtime environment.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for live container runtime analysis, mounted secrets, sidecars, namespaces, init containers, entrypoint drift, and route-to-container resolution. Use when the user asks why a live container differs from manifests, where a mounted secret is consumed, how a sidecar or init container changes runtime state, or which route resolves to which live container. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Run the restored Claude Code agent runtime with GitHub Models or Copilot providers for local AI coding workflows
Internal helper contract for calling the pi-companion runtime from Claude Code
Uses get_runtime_errors and lsp to fetch an active stack trace, locate the failing line, apply a fix, and verify resolution via hot_reload.
Debug and verification workflow for runtime-bundle and module-resolution regressions. Use when diagnosing unexpected module inclusions, bundle size regressions, or CI failures related to NEXT_SKIP_ISOLATE, nft.json traces, or runtime bundle selection (module.compiled.js). Covers CI env mirroring, full stack traces via __NEXT_SHOW_IGNORE_LISTED, route trace inspection, and webpack stats diffing.
Manage host-mode duoduo runtime settings and diagnostics. Use when the user asks to inspect or change daemon status, daemon config, daemon logs, Codex runtime enablement, debug log level, telemetry persistence, cadence frequency, or other persistent host-mode settings stored in ~/.config/duoduo/.env. Also trigger for Chinese requests such as 帮我启用 codex runtime, 打开 debug log, 关闭 telemetry, 调 cadence 频率, or 看看 duoduo daemon 配置.
Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.