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2,024 Results in Skills, Hooks, Observability, Sub-Agents · Page 61 of 85

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pyvene-interventions

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.

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mechanistic-interpretability-pyveneskills
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qa

QA Agent. Tests all acceptance criteria and edge cases from orchestrator-output.md. Generates a structured qa-report.md with pass/fail per criterion and bug triage. Loops back to implement if bugs found (max 2 iterations).

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agentssubagents
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qa-coordinator

PROACTIVELY USE this agent when you need to establish quality assurance processes, coordinate testing activities, define quality standards, or ensure deliverables meet quality requirements throughout the project lifecycle. This agent MUST BE USED for quality assurance and testing coordination tasks. Examples: <example>Context: User wants to ensure their software project maintains high quality standards throughout development. user: 'We need to establish quality processes for our new product development to ensure we deliver bug-free software' assistant: 'I'll use the qa-coordinator agent to establish comprehensive quality assurance processes and testing strategies for your project.' Since the user needs to establish quality processes and testing coordination, use the qa-coordinator agent to create comprehensive QA strategies.</example> <example>Context: User has completed a feature and needs quality gates established before deployment. user: 'I've finished implementing the user authentication module. What quality checks should we run before releasing it?' assistant: 'Let me use the qa-coordinator agent to define the appropriate quality gates and testing strategy for your authentication module.' Since the user needs quality assurance guidance for a specific deliverable, use the qa-coordinator agent to establish testing protocols.</example>

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dlezosubagents
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qa-expert

Use this agent when you need comprehensive quality assurance strategy, test planning across the entire development cycle, or quality metrics analysis to improve overall software quality.

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quality-securitysubagent
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qa-test-planner

Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.

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qdrant-vector-search

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

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rag-qdrantskills
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qiskit

Comprehensive quantum computing toolkit for building, optimizing, and executing quantum circuits. Use when working with quantum algorithms, simulations, or quantum hardware including (1) Building quantum circuits with gates and measurements, (2) Running quantum algorithms (VQE, QAOA, Grover), (3) Transpiling/optimizing circuits for hardware, (4) Executing on IBM Quantum or other providers, (5) Quantum chemistry and materials science, (6) Quantum machine learning, (7) Visualizing circuits and results, or (8) Any quantum computing development task.

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qiskitskills
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qms-audit-expert

Senior QMS Audit Expert for internal and external quality management system auditing. Provides ISO 13485 audit expertise, audit program management, nonconformity identification, and corrective action verification. Use for internal audit planning, external audit preparation, audit execution, and audit follow-up activities.

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quality-documentation-manager

Senior Quality Documentation Manager for comprehensive documentation control and regulatory document review. Provides document management system design, change control, configuration management, and regulatory documentation oversight. Use for document control system implementation, regulatory document review, change management, and documentation compliance verification.

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quality-manager-qmr

Senior Quality Manager Responsible Person (QMR) for HealthTech and MedTech companies. Provides overall quality system responsibility, regulatory compliance oversight, management accountability, and strategic quality leadership. Use for quality system governance, regulatory compliance oversight, management responsibility, and quality strategic planning.

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quality-manager-qms-iso13485

ISO 13485 Quality Management System specialist for medical device companies. Provides QMS implementation, maintenance, process optimization, and compliance expertise. Use for QMS design, documentation control, management review, internal auditing, corrective actions, and ISO 13485 certification activities.

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quality-manager-qms-iso13485skills
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quality-nonconformance

Codified expertise for quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycl…

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quant-analyst

Use this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, or conduct advanced risk analytics for derivatives and portfolios. Invoke this agent for statistical arbitrage strategy development, backtesting with historical validation, derivatives pricing models, and portfolio risk assessment.

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specialized-domainssubagent
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quant-analyst-2

Use this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, or conduct advanced risk analytics for derivatives and portfolios. Invoke this agent for statistical arbitrage strategy development, backtesting with historical validation, derivatives pricing models, and portfolio risk assessment. Specifically:\\n\\n<example>\\nContext: A hedge fund wants to develop a statistical arbitrage strategy exploiting mean reversion patterns in equity pairs.\\nuser: \"We've identified potential mean reversion signals in 500 equity pairs. Can you develop a statistical arbitrage strategy with robust backtesting and risk controls?\"\\nassistant: \"I'll conduct cointegration analysis on your pairs, develop a mean-reversion trading model with optimal position sizing, execute comprehensive backtesting over 10+ years with walk-forward validation, quantify risk metrics (Sharpe ratio, max drawdown, VaR), and implement dynamic stop-loss and portfolio hedging strategies. I'll deliver a fully tested strategy with performance attribution and market microstructure analysis.\"\\n<commentary>\\nUse this agent when you need to build production-ready trading strategies grounded in statistical rigor, featuring comprehensive backtesting, risk controls, and performance validation across market regimes.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: A financial institution needs to price exotic derivatives and analyze their risk exposure across multiple underlying assets.\\nuser: \"We need to price European and American barrier options on commodity futures, calculate their Greeks for hedging, and stress-test across volatility scenarios for regulatory reporting.\"\\nassistant: \"I'll implement Monte Carlo pricing for barrier options with variance reduction techniques, calculate all Greeks analytically and numerically, build volatility surface models from market data, conduct comprehensive stress testing across scenarios (volatility shocks, correlation breaks, liquidity shifts), and generate VaR and CVaR metrics for regulatory compliance and risk reporting.\"\\n<commentary>\\nInvoke this agent for complex derivatives pricing, Greeks calculation, and multi-dimensional risk analytics when you need mathematical rigor, regulatory compliance, and sophisticated valuation models.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: A quantitative fund needs to optimize their portfolio allocation balancing return objectives against risk constraints and regulatory requirements.\\nuser: \"Optimize our 200-asset portfolio using Black-Litterman framework. Account for transaction costs, position limits, sector constraints, and minimize tail risk while targeting 12% annual returns.\"\\nassistant: \"I'll implement Black-Litterman optimization incorporating your views and priors, build efficient frontiers under transaction cost and constraint regimes, apply factor risk analysis to identify exposures, conduct Monte Carlo simulations for drawdown distribution, backtest portfolio allocations through market stress periods (2008 crisis, COVID, rate hikes), and deliver dynamic rebalancing triggers with slippage analysis.\"\\n<commentary>\\nUse this agent when building sophisticated portfolio optimization frameworks that require multi-objective optimization, constraint handling, factor analysis, and stress testing against historical and hypothetical scenarios.\\n</commentary>\\n</example>

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financesubagents
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quantizing-models-bitsandbytes

Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.

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optimization-bitsandbytesskills
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quarkus-patterns

Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures.

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quarkus-security

Quarkus Security best practices for authentication, authorization, JWT/OIDC, RBAC, input validation, CSRF, secrets management, and dependency security.

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quarkus-tdd

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

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quarkus-verification

"Verification loop for Quarkus projects: build, static analysis, tests with coverage, security scans, native compilation, and diff review before release or PR."

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query-clarifier

Use this agent when you need to analyze research queries for clarity and determine if user clarification is needed before proceeding with research. This agent should be invoked at the beginning of research workflows to ensure queries are specific and actionable. Examples: <example>Context: The user has created a query-clarifier agent to analyze research queries for clarity. user: "Tell me about AI" assistant: "I'll use the query-clarifier agent to analyze this query for clarity and determine if we need more specific information." <commentary>Since the query is quite broad and could refer to many aspects of AI, the query-clarifier agent should analyze it and likely request clarification about which specific aspect of AI the user is interested in.</commentary></example> <example>Context: The user has created a query-clarifier agent to ensure research queries are actionable. user: "Compare the performance of different sorting algorithms in terms of time complexity" assistant: "Let me analyze this query with the query-clarifier agent to ensure it's clear and specific enough for research." <commentary>This query is relatively clear but the agent should still analyze it to confirm no clarification is needed before proceeding with the research.</commentary></example>

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deep-research-teamsubagents
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qutip

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

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qutipskills
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raffle-winner-picker

Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

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raffle-winner-pickerskills
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rag-engineer

Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, document retrieval.

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rag-engineerskills
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rag-implementation

Retrieval-Augmented Generation patterns including chunking, embeddings, vector stores, and retrieval optimization Use when: rag, retrieval augmented, vector search, embeddings, semantic search.

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rag-implementationskills
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