「eval」の検索結果

Strategic advisor for Evvo Labs business decisions. Use when Vince asks for strategic advice, business opinions, market entry decisions, pricing strategy, product prioritization, resource allocation, partnership evaluation, competitive positioning, or any question about what Evvo should do next. Applies 5 frameworks: VRIO (competitive advantage), Value Stick (pricing/margin), Blue Ocean (market positioning), McKinsey Horizons (resource allocation), Strategy Diamond (initiative planning). Always read references/evvo-strategy.md before advising.

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Evaluate and prioritize opportunities through a structured filtering process. Use for resource allocation, strategic decision support, and project management.

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Framework-directable information security risk assessment. Identifies threats, evaluates likelihood/impact via a 3x3 matrix, maps findings to any compliance framework, and recommends risk treatment options with prioritization guidance.

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Evaluate strategic options by NPV vs ease of implementation. Use for project prioritization, resource allocation, and strategic decision making.

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Conduct exhaustive multi-source investigation with methodology tracking, source evaluation, and iterative depth.

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Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.

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Understand blockchain technology, interact with smart contracts, and evaluate when distributed ledgers solve real problems.

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Offers, compensation framing, and negotiation planning. Use when evaluating offers or raises.

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Comprehensive Power BI data model design review prompt for evaluating model architecture, relationships, and optimization opportunities.

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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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INVOKE THIS SKILL when optimizing, improving, or debugging LLM prompts using production trace data, evaluations, and annotations. Covers extracting prompts from spans, gathering performance signal, and running a data-driven optimization loop using the ax CLI.

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INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI.

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Secure secrets handling in Ansible with Infisical vault integration, no_log directive enforcement, and a reusable Infisical lookup task for safe credential retrieval.

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Evaluate current session for skill-worthy workflows and create reusable skills. Triggers on: auto-skill, create skill from session, save workflow, capture this as a skill.

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Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer, and autonomous agents. Includes pattern combinations and language-specific implementations.

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Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.

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Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

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Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. Supports CLI and MCP integration.

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Build accretion/dilution (merger) models in Excel — pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation.

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Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

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Reference definitions for the Agent Forge orchestration roles (lead, worker, planner, evaluator). Use when coordinating multi-agent Forge work or when you need one role's responsibilities and constraints.

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Run the full Forge pipeline unattended: each phase is reviewed by a fresh evaluator subagent, the findings feed back, and the run advances itself. Use when the user runs /forgemaster-auto or wants a feature built end to end without approval gates.

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Grade and steer UI work using Anthropic-style design dimensions—coherence, originality, craft, and usability—for generators and evaluators.

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Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Use PROACTIVELY for vector search implementation, embedding optimization, or semantic retrieval systems.

日本語の概要は準備中です。原文の説明を表示しています。