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Found 197 Skills
Configure LangWatch online evaluations and guardrails for production traffic. Use when the user wants to score live traces or threads, monitor production quality, sample incoming traffic, or synchronously block unsafe requests and responses. Do not use for batch experiments.
Build and operate multi-agent workflows with OpenAI Agents SDK (Python): define agents/tools/handoffs, add guardrails, run conversations, and debug orchestration behavior. Use when users ask for agent orchestration with OpenAI-native patterns, handoff routing, or production-ready agent loops.
Interactive session to craft a system prompt for an AI agent powered by the Sanity Context MCP server. Use this skill when users want to define agent personality, set tone/voice, establish boundaries and guardrails, configure refusal behaviors, or control how their agent communicates. Trigger when users mention their agent sounds wrong, needs to refuse certain requests, has the wrong tone, or they want to set communication rules and policies.
Set up Superagent Context Guardrails at coding-agent tool boundaries, configure and safely use the remote MCP server, and manage signed webhooks for findings, security reports, Contributor Trust, and Runtime Guardrails. Use when the user asks to enable context scanning before an agent consumes URLs, files, email, skills, or MCP repositories; integrate coding-agent hooks; or install, connect, configure, troubleshoot, or operate Superagent from Cursor, Claude Code, Codex CLI, or another MCP client.
Migrate Python OpenAI Agents SDK applications to Pydantic AI and, when warranted, Pydantic AI Harness. Use for `agents.Agent`, `Runner`, function tools, handoffs, guardrails, sessions, human approval, streaming, or `SandboxAgent`. Do not use for applications built directly on the OpenAI Responses API without the Agents SDK runtime.
Set the organisation's top-level paid-media spend guardrails as written policy - maximum allowable CAC, minimum ROAS/MER floor, kill-switch thresholds, counter-metrics, who owns them and who may override them - each derived from contribution margin, payback, and cash runway rather than inherited from a dashboard. Use whenever the user asks what CAC they can afford, mentions a ROAS floor, spend guardrails, a kill switch, when to stop spending, or who approves a budget increase - even if they never say 'guardrails'. Covers B2B and B2C. Do NOT use to judge whether current CAC/ROAS is actually good (mbfinotti/advertising-skills@cac-roas-benchmark) or to monitor daily pacing (mbfinotti/advertising-skills@ad-budget-pacing).
Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I/O-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I/O-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.
Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.
Vendor-neutral skill to generate a staged feature-flag rollout plan (phases, metrics, guardrails, rollback criteria) from feature context and risk inputs.
Authors, reviews, installs, and debugs GitHub Agentic Workflows in repositories, including workflow markdown, frontmatter, gh aw compile and run flows, safe outputs, security guardrails, and operational patterns. Use when creating or maintaining GH-AW automation. Don't use for standard deterministic GitHub Actions YAML, generic CI pipelines, or non-GitHub automation systems.