AgentX - Digital Force for Software Delivery
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Skill Claude CodeCodex
Design agent memory beyond a single context window: short-term (working / scratchpad), long-term (episodic, semantic, procedural), and shared / cross-session memory. Covers mem0, Zep, Letta / MemGPT, LangMem, OpenAI Memory, retrieval and consolidation policies, PII handling, and eviction.
Skill Claude CodeCodex
Instrument LLM agents with tracing, metrics, and evaluation telemetry. Use when adding OpenTelemetry GenAI semantic conventions, integrating Langfuse / LangSmith / Arize Phoenix / Helicone / OpenLLMetry, capturing prompt/response spans, tool-call latency, token cost, eval scores, and feedback signals. Distinct from…
Skill Claude CodeCodex
Build production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production deployment.
Skill Claude CodeCodex
Use when evaluating AI quality, safety, completeness and cost with held-out tasks, executable graders, calibrated judges and explicit release criteria.
Skill Claude CodeCodex
Defend LLM systems against prompt injection, jailbreaks, data exfiltration, and unsafe output. Covers input/output guardrails (NeMo Guardrails, LlamaGuard 3, ShieldGemma, Azure AI Content Safety, Bedrock Guardrails), red-team frameworks (Microsoft PyRIT, Garak, promptfoo redteam), and Responsible AI controls…
Skill Claude CodeCodex
Implement production applications with Anthropic Claude models -- Messages API, tool use, prompt caching, adaptive thinking, vision, computer use, and the Claude Agent SDK. Use when coding directly against Anthropic APIs, Claude via AWS Bedrock, or Claude via GCP Vertex AI rather than a higher-level framework.
Skill Claude CodeCodex
Design and architect AI agents on Azure AI Foundry -- lifecycle planning, model selection strategy, evaluation frameworks, guardrail design, and deployment patterns. Use when designing agent architecture on Foundry, choosing models, planning evaluation strategy, or defining guardrails. For step-by-step operational…
Skill Claude CodeCodex
Design and implement the cognitive architecture of AI agents including memory systems, RAG pipelines, and state management. Use when defining agent memory strategy (short/long-term), building RAG pipelines (knowledge retrieval), designing state management systems, or selecting vector databases for semantic search.
Skill Claude CodeCodex
Build agents that operate browsers and desktop GUIs via screenshots and actions. Covers Anthropic Computer Use, OpenAI Operator / Computer-Using Agent (CUA), browser-use, Playwright-based agents, sandboxing (containers, VM, ephemeral profiles), permissions and approvals, failure recovery, and testing patterns.
Skill Claude CodeCodex
Manage LLM context windows efficiently. Use when implementing context compaction, conversation summarization, token budget management, sliding window strategies, or optimizing prompt length for cost and quality.
Skill Claude CodeCodex
Design strategies to detect, monitor, and remediate data drift in GenAI applications and ML pipelines. Use when monitoring LLM input patterns, detecting query distribution shifts, tracking embedding drift, building RAG retrieval quality monitoring, or establishing data governance for model inputs.
Skill Claude CodeCodex
Design and implement feedback loops for continuous AI/ML improvement. Use when building RLHF/RLAIF pipelines, user feedback collection systems, reward modeling, iterative model refinement workflows, or online learning strategies.
Skill Claude CodeCodex
Implement agentic applications with the Microsoft Foundry SDKs. Use when coding against Microsoft Foundry project clients, agent operations, evaluations, datasets, indexes, tracing, or SDK-driven tool wiring rather than only high-level architecture guidance.
Skill Claude CodeCodex
Operate generative AI systems safely in production. Use when designing GenAIOps workflows for prompt and model release management, evaluation gates, observability, drift detection, rollback, governance, and continuous improvement.
Skill Claude CodeCodex
Progressive context refinement for subagents and tool-using LLMs. Use when a parent agent must delegate research, code reading, or document Q&A to a subagent with a tight context budget. Replaces one-shot context dumps with a query -> retrieve -> filter -> requery loop that returns only the evidence the parent needs.
Skill Claude CodeCodex
Build stateful, durable agent workflows with LangGraph. Use when implementing graph-based orchestration, long-running agent state, human-in-the-loop checkpoints, subgraphs, memory, or LangSmith-observed agent execution.
Skill Claude CodeCodex
Front LLM calls behind a gateway: model routing, fallbacks, semantic caching, rate limits, key vaulting, cost controls, and unified APIs. Covers LiteLLM, Portkey, Azure AI Gateway / APIM, OpenRouter, AWS Bedrock proxy, and self-built gateways. Includes routing policies (cost/latency/capability/RBAC) and caching (exact…
Skill Claude CodeCodex
Build MCP Apps (ext-apps) that render interactive UI inside conversational AI clients. Use when creating visual tool outputs, interactive dashboards, form-based tools, or rich media experiences in MCP-compatible hosts like Claude Desktop, VS Code Copilot Chat, or other MCP clients that support the Apps specification.
Skill Claude CodeCodex needs its repo
Build Model Context Protocol (MCP) servers that expose tools, resources, and prompts to AI agents. Use when creating MCP servers in TypeScript or Python, defining MCP tools, implementing resource providers, or integrating MCP servers with AI agent workflows.
Skill Claude CodeCodex
Detect, monitor, and manage model drift in production GenAI and ML systems. Use when monitoring LLM output quality, detecting prompt regression, managing model version changes, implementing drift detection for traditional ML, or establishing model governance policies.
Skill Claude CodeCodex
Fine-tune foundation models for domain-specific tasks. Use when adapting LLMs with LoRA/QLoRA/PEFT, full fine-tuning, knowledge distillation, or designing training data pipelines for model customization.
Skill Claude CodeCodex
Design and operate multi-agent systems where several specialized LLM agents collaborate. Use when choosing between supervisor/worker, swarm/handoff, hierarchical, or graph patterns; selecting frameworks (AutoGen, CrewAI, OpenAI Swarm/Agents SDK, LangGraph, Microsoft Agent Framework, Google A2A); designing handoff…
Skill Claude Code
Use when designing coding-agent prompts, tool contracts, structured outputs and model-adaptive context, or evaluating prompt changes.
Skill Claude CodeCodex
Version, test, promote, and roll back prompts like production artifacts. Use when managing prompt lifecycle, prompt variants, few-shot changes, rubric alignment, baseline comparisons, and safe prompt release workflows across models or environments.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: