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Found 6,510 Skills
Drive the Duvo public API from the terminal via the `duvo` CLI (`@duvoai/cli`). Use when the user wants to script Duvo — managing agents, runs, cases, queues, files, skills, connections, Clarity processes, or hitting an arbitrary endpoint via `duvo api` — instead of clicking through the Duvo web UI or hand-crafting `curl` calls.
Review generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).
Salesforce Data Cloud Act phase. Use this skill when the user manages activations, activation targets, data actions, or downstream delivery of Data Cloud audiences and data. TRIGGER when: user manages activations, activation targets, data actions, or downstream delivery of Data Cloud audiences and data. DO NOT TRIGGER when: the task is segment creation (use data360-segment), data retrieval/search work (use data360-query), or STDM/session tracing (use agentforce-observe).
Salesforce Data Cloud Connect phase. Use this skill when the user manages Data Cloud connections, connectors, or sets up a new source system. TRIGGER when: user manages Data Cloud connections, connectors, connector metadata, tests a connection, browses source objects or databases, or sets up a new source system. DO NOT TRIGGER when: the task is about data streams or DLOs (use data360-prepare), DMOs or identity resolution (use data360-harmonize), retrieval/search (use data360-query), or STDM telemetry (use agentforce-observe).
Survey a whole React codebase as a senior React engineer, using React Doctor's scan as evidence, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the React code", "audit this codebase", "make this app faster / more robust", or wants a roadmap of fixes rather than a review of a single diff. For a regression check or a fix-it-now pass, use the `react-doctor` skill instead.
Writes, rewrites, diagnoses, and improves any LLM prompt with minimal, high-signal edits. Use when the user wants to create a new prompt from scratch, review or fix a prompt that produces poor output, simplify or tighten instructions, restructure a long prompt, port a prompt between models, or expand an existing prompt. Covers system prompts, agent instructions, CLAUDE.md rules, SKILL.md prompt bodies, chat templates, structured-output prompts, RAG context templates, and prompt strings embedded in code. Also use when editing any file whose primary content is LLM instructions.
Use when interacting with Unity CLI from the terminal — install, upgrade or uninstall editors, create, list or open projects, manage modules, manage licenses, check auth status, read logs, browse Unity releases, build/test projects, configure the Unity MCP server for AI agents, or run any other Unity CLI operation. For a guided idea-to-running-project flow for a brand-new game, use the new-unity-project skill instead.
Use when writing git commit messages for non-trivial changes — captures decision context (constraints, rejected alternatives, confidence, directives) as structured git trailers so future agents and developers can query project knowledge via git log --trailer=
Guides agents in compiling and packaging C/C++ source code into dynamic or static libraries (Code Assets) using Dart's Native Assets hook system (via hook/build.dart and hook/link.dart utilizing package:hooks and package:native_toolchain_c). Use when a user asks to: 'setup native assets', 'compile C/C++ source code', 'bundle dynamic libraries', 'build native C code', 'link native assets', 'implement build.dart or link.dart hooks', or 'integrate C/C++ interop in Dart/Flutter'. Helps agents avoid manual toolchain orchestration and configures secure hash-validated binary downloads or advanced linker tree-shaking with package:record_use mapping.
Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
Recommend webhook subscriptions and safe automation patterns for PlanetScale alerts, anomalies, schema recommendations, deploy requests, and agent workflows.
Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.