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Found 197 Skills
CrewAI task design and configuration. Use when creating, configuring, or debugging crewAI tasks — writing descriptions and expected_output, setting up task dependencies with context, configuring output formats (output_pydantic, output_json, output_file), using guardrails for validation, enabling human_input, async execution, markdown formatting, or debugging task execution issues.
Choose the right metrics for a LaunchDarkly experiment, guarded rollout, or release policy. Use when the user wants to know which metrics to use, which is the primary metric for an experiment, what guardrails to add, or which events to monitor in a rollout. Surfaces what will auto-attach from existing release policies before making additional recommendations.
Create and run LangWatch experiments for pre-deployment batch testing. Use when the user wants to test an agent against a dataset, compare prompts or models, benchmark quality, detect regressions, or add a CI quality gate. Do not use for production monitoring or guardrails.
Discover and execute repository test commands safely with evidence-based command selection and safety guardrails.
Use this skill when the user wants to spend money, make purchases, send crypto, pay for APIs, browse websites for shopping, complete checkout, or manage an AI agent's payment wallet. Covers buying products online with credit cards (including browser-automated checkout), sending tokens, paying for x402 protocol APIs, checking balances, depositing funds, browsing available services, and signing on-chain transactions — all with secure guardrails, and appropriate human controls. Trigger on any spending, wallet, or shopping intent: "buy this", "pay for that", "send tokens", "how much do I have", "what can I buy", "top up my wallet", "get a card", "set up payments", "find me something to buy", "complete the checkout", or "browse that site" — even if the user doesn't mention "lobster", "crypto", or "Solana" directly.
Find every way users can break your AI before they do. Use when you need to red-team your AI, test for jailbreaks, find prompt injection vulnerabilities, run adversarial testing, do a safety audit before launch, prove your AI is safe for compliance, stress-test guardrails, or verify your AI holds up against adversarial users. Covers automated attack generation, iterative red-teaming with DSPy, and MIPROv2-optimized adversarial testing.
Draft the creative campaign brief a brand hands to an already-signed influencer or creator for one campaign - deliverables with exact specs, key messages with proof points, brand guardrails, disclosure requirements, timeline, and bounded review rounds, split into non-negotiables vs preferences. Covers B2C brand collabs and B2B creator programs. Use whenever the user mentions a creator brief, campaign brief, content brief, creator deliverables, or briefing a creator they just signed, even if they never say brief. Starts after the deal is signed and reflects its terms exactly. Do NOT use for picking or vetting the creator - use mbfinotti/partnerships-skills@influencer-discovery-brief instead.
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).
Run browser automation through @playwright/mcp over UXC stdio MCP, with daemon-friendly session reuse and safe action guardrails. Use when tasks need deterministic page navigation, DOM snapshots, and scripted browser interaction from CLI.
How to create, manage, and use Ethereum wallets. Covers EOAs, smart contract wallets, multisig (Safe), and account abstraction. Essential for any AI agent that needs to interact with Ethereum — sending transactions, signing messages, or managing funds. Includes guardrails for safe key handling.
Operate Feishu or Lark IM APIs through UXC with a curated OpenAPI schema, tenant-token bearer auth, and chat/message guardrails.
Operate DingTalk messaging APIs through UXC with a curated OpenAPI schema, app-token bearer auth, and robot/service-group guardrails.