2.1K skills · sorted by relevance
Explore World Cup match predictions, related news, and market probabilities. Adjust model factors to compare possible outcomes, then optionally hand off to Binance Agentic Wallet for prediction-market trading, where orders require an explicit choice and confirmation.
Review an AI agent codebase against ten OWASP ASI security risk areas. Examine tool permissions, input validation, identity checks, audit logs, and other controls, then summarize coverage, gaps, and recommended improvements in a report.
Design a Google Cloud system for data analysis or machine learning with AI agents. Turn requirements into product choices, an architecture diagram, infrastructure configuration, deployment instructions, and validation steps, with user reviews between phases.
Review GitHub agentic workflows, automated workflows guided by AI agents, for security and correctness. Compile changes, inspect permissions and safeguards, and use available run logs to identify supported improvements to cost and execution time.
Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
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Install or update the agentic-stack portable brain in the current project, then verify it. Read by an agent; no human steps required.
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Knowledge base from "Solving a Million-Step LLM Task with Zero Errors" (Meyerson, Paolo, Dailey, Shahrzad, Francon, Hayes, Qiu, Hodjat, Miikkulainen — arXiv:2511.09030). Use when designing long-horizon, multi-step agentic LLM pipelines that need very high reliability, applying Maximal Agentic Decomposition (MAD), first-to-ahead-by-k voting, or red-flagging error correction, estimating cost/reliability scaling laws for multi-agent systems, or studying Massively Decomposed Agentic Processes (MDAPs).
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Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
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Audit a website against the Forter Agentic Readiness Guide. Loads the 25 weighted rubrics in `audit/`, probes the target site (and optional source code), scores each guideline Pass/Partial/Fail/N/A with sub-check granularity, and produces a prioritized fix report. Use when a user asks "score my site against the agentic readiness guide", "audit https://… for agent readiness", or "what do I need to fix to be agent-ready".
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Plan, implement, or review agentic eval work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests agentic eval work.
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Expert guide for AI-assisted coding workflows — agentic code generation, multi-agent code swarms, self-healing CI/CD, automated PR review, spec-to-code pipelines, codebase knowledge graphs, and human-in-the-loop approval gates / Panduan ahli untuk workflow pengkodean berbasis AI — generasi kode agentic, code swarm multi-agen, CI/CD self-healing, review PR otomatis, pipeline spec-to-code, knowledge graph codebase, dan gate persetujuan human-in-the-loop.
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Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
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Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.
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Agent skill for agentic-payments - invoke with $agent-agentic-payments
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Scaffold Quarkus + LangChain4j projects end-to-end and add agentic components to existing ones — AI services, tools, agents and multi-agent workflows, RAG pipelines, MCP clients and servers (Model Context Protocol), guardrails, and embedding store setups. Use this whenever the user wants a new Quarkus + LangChain4j project or module created, or an agentic component added to an existing project in this stack, including a baseline pom.xml, application.properties, project layout, or starter classes.
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Audit an existing Quarkus + LangChain4j project against this stack's agentic conventions — a read-only conformance or gap-analysis review. Use when the user asks to audit, review, check, assess, or validate a Quarkus project against the LangChain4j agentic conventions, or wants to know whether an existing project conforms to (or is ready to adopt) this stack. User-invoked only.
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Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.
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Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).
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Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).
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Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.
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Audit codebases, infrastructure, AND agentic AI systems for security issues. Covers traditional security (dependencies, secrets, OWASP web top 10, SSL/TLS, file permissions) PLUS agentic security (prompt injection scanning, identity spoofing detection, memory poisoning checks, multi-agent communication audit, OWASP Agentic Top 10). Use when scanning for vulnerabilities, detecting hardcoded secrets, reviewing agent workspace configuration, checking prompt injection vectors, or auditing agent permissions and boundaries.
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Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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