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Found 5,583 Skills
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
Search Sourcegraph-indexed codebases for patterns, examples, and system understanding. Triggers on implementation questions, debugging, or "how does X work" queries.
An analytical in-process SQL database management system. Designed for fast analytical queries (OLAP). Highly interoperable with Python's data ecosystem (Pandas, NumPy, Arrow, Polars). Supports querying files (CSV, Parquet, JSON) directly without an ingestion step. Use for complex SQL queries on Pandas/Polars data, querying large Parquet/CSV files directly, joining data from different sources, analytical pipelines, local datasets too big for Excel, intermediate data storage and feature engineering for ML.
Guide for Direct Memory Access (DMA) attack techniques using FPGA hardware. Use this skill when researching PCIe DMA attacks, pcileech, FPGA firmware development, or hardware-based memory access for game security research.
Generate context-aware quality checklists for code review and QA using IEEE 1028 base standards plus LLM contextual additions
Template-driven workflow coordinator with minimal state tracking. Executes command chains from workflow templates OR unified PromptTemplate workflows. Supports slash-command and DAG-based execution. Triggers on "flow-coordinator", "workflow template", "orchestrate".
A professional tool for generating customized checklists for current features based on user requirements. Specifically designed for requirement quality validation, it creates "English-style unit tests" to verify the completeness, clarity, and consistency of requirements. Trigger words: speckit-checklist, checklist, requirements validation, quality check, quality review, spec review
Automatically fix ESLint errors by modifying code to comply with linting rules. For small codebases (≤20 errors), fixes directly. For larger codebases (>20 errors), spawns parallel agents per directory for efficient processing. Never disables rules or adds ignore comments.
Comprehensive guide and utilities for building AI agents using the Agent2Agent (A2A) Protocol. Use when implementing agent-to-agent communication, creating A2A servers/clients, or working with JSON-RPC based agent systems.
Search and retrieve Google's developer documentation using the Developer Knowledge API. Query documentation chunks, get full document content, or batch retrieve multiple documents. Covers ai.google.dev, developer.android.com, docs.cloud.google.com, firebase.google.com, and more.
Amazon Bedrock Agents for building autonomous AI agents with foundation model orchestration, action groups, knowledge bases, and session management. Use when creating AI agents, orchestrating multi-step workflows, integrating tools with LLMs, building conversational agents, implementing RAG patterns, managing agent sessions, deploying production agents, or connecting knowledge bases to agents.
Expertise in Go programming according to the Google Go Best Practices. Focuses on actionable advice for naming, error handling, performance, testing, and general idiomatic Go to ensure high-quality, maintainable, and efficient codebases.