Expert-level C++ development with modern C++20/23, STL, memory management, and performance
Use when working with modern C++ codebases requiring features from C++11 to C++23 including lambdas, move semantics, ranges, and concepts.
Use when managing memory safely in C++ with smart pointers including unique_ptr, shared_ptr, weak_ptr, and RAII patterns.
Use when creating generic and type-safe C++ libraries with templates, SFINAE, concepts, and compile-time metaprogramming.
Implement CQRS in Symfony with separate Command and Query buses/handlers using the Messenger component
Generates git commit messages following conventional commit standards with collaborative attribution.
Crash simulation setup and analysis for occupant protection and regulatory compliance
Design and then create a board (dashboard) in Honeycomb with queries and SLOs. Trigger phrases: "create a board", "make a board", "build a dashboard", "create a Honeycomb board",…
Use when asked to create an automation loop or automate a recurring task with an FSM.
Create voice profiles from writing samples.
Create or confirm the compliant working branch for the current approved plan before implementation begins.
Analyze project artifacts and generate a populated CONTEXT.md (or CONTEXT-MAP.md and multiple CONTEXT.md files for multi-context repos) with domain terms extracted from existing…
Predicts potential off-target sites for a given sgRNA sequence using mismatch analysis. — from bg-szy/TOP-SKILLS
Predicts potential off-target sites for a given sgRNA sequence using mismatch analysis. — from general/general-misc
Critical Chain Project Management (CCPM) skill with buffer management and resource leveling
Perform critical path method (CPM) analysis with forward/backward pass calculations
Flow-through logistics process coordination skill to minimize storage time and accelerate product movement
Coordinate changes across project-beta repositories when updating runner configurations. Ensures workflow labels match runner scale set names.
Crystallization process design skill for nucleation control, crystal size distribution, and equipment selection
Advanced skill for crystallographic structure analysis and determination including space group identification, atomic position refinement, and PDF analysis
CS 시리즈 CEO 오케스트레이터. 자연어 요청을 받아 공수 추정 후 CS-test/CS-plan/CS-codebase-review/cs-design/cs-smart-run 중 최적 조합을 자율 선택·배분한다. Use when user types "/cs-ceo" or "cs-ceo".
C-suite executive decision support: strategy, technology, growth, competitive intelligence, project evaluation.
Submit to App Store, App Store rejection, Apple guidelines, ready to ship. App Store submission compliance and Human Interface Guidelines.
Chemical/Physical Vapor Deposition skill for thin film and nanostructure deposition optimization
AI-driven cycle counting schedule and variance analysis skill to maintain inventory accuracy with minimal operational disruption
Cycle time analysis and reduction skill with process timing, bottleneck identification, and flow improvement
AI-powered cytokine release syndrome (CRS) and cytokine storm analysis for prediction, monitoring, and management in immunotherapy and infectious disease.
Nanotoxicology skill for in vitro cytotoxicity assessment and cell viability analysis
Runtime-health view of the four fleet daemons — phone bridge, notifyd, ATC, and the fleet auto-continue daemon — in one table.
Ranks skill matches by fit, performance history, and contextual relevance. Applies multi-factor scoring including success rate, resource usage, and task alignment.
Assigns confidence scores to agent outputs based on multiple factors including source quality, consistency, and reasoning depth. Produces calibrated confidence estimates.
Manages context passing between DAG nodes and spawned agents. Handles context summarization, selective forwarding, and token budget optimization.
Tracks iteration progress toward task completion goals. Monitors quality trends, detects plateauing, and recommends when to stop iterating.
Validates DAG structures, performs topological sorting, detects cycles, and resolves dependency conflicts. Uses Kahn's algorithm for optimal execution ordering.
Modifies DAG structure during execution in response to failures, new requirements, or runtime discoveries. Supports node insertion, removal, and dependency rewiring.
Traces complete execution paths through DAG workflows. Records timing, inputs, outputs, and state transitions for all nodes.
Performs root cause analysis on DAG execution failures. Traces failure propagation, identifies systemic issues, and generates actionable remediation guidance.
Synthesizes actionable feedback from validation results, confidence scores, and iteration triggers. Creates structured improvement guidance for re-execution.
Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and…
Detects fabricated content, false citations, and unverifiable claims in agent outputs. Uses source verification and consistency checking.
Manages agent isolation levels and resource boundaries. Configures strict, moderate, and permissive isolation profiles.
Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies.
The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically…
Validates agent outputs against expected schemas and quality criteria. Ensures outputs meet structural requirements and content standards.
Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination.
Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations.
Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations.
Profiles DAG execution performance including latency, token usage, cost, and resource consumption. Identifies bottlenecks and optimization opportunities.
Combines and synthesizes outputs from parallel DAG branches. Handles merge strategies, conflict resolution, and result formatting.
Matches natural language task descriptions to appropriate skills using semantic similarity. Handles fuzzy matching, intent extraction, and capability alignment.
Central catalog of available skills with metadata, capabilities, and performance history. Provides skill discovery and lookup services.
Wave-based parallel scheduling for DAG execution. Manages execution order, resource allocation, and parallelism constraints.
Use when the user asks about cost, spending, or budget — e.g. 'how much did I spend today', 'daily cost', 'cost report', 'what's my spend
Generate personalized verified news briefs with 7-day freshness and 95%+ source accuracy
Export query results to various formats (CSV, JSON, Excel, Markdown tables) with proper formatting and headers. Use when saving analysis results to files.
Database design and migration patterns for Alembic migrations, schema design (SQL/NoSQL), and database versioning.
Expert-level Databricks platform, Apache Spark, Delta Lake, MLflow, notebooks, and cluster management
Database performance audit — detects N+1 queries, missing indexes, join opportunities, slow queries, EXPLAIN analysis, and per-endpoint DB call counts.
Analyze database query performance with execution plans and index recommendations
開発用 MySQL データベースを完全リセットしシードデータを再投入する。 「DB をリセットして」「データを初期化して」「テストデータを入れ直して」 「データが壊れたのでクリーンにしたい」などのリクエストで使用する。 全データが削除される破壊的操作のため必ずユーザー確認を取ってから実行する。 本番環境では絶対に使用しない。手動実行専用。