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Found 3,443 Skills
Install the AgentHog SDK and wire tracing into the project — init at startup, wrap the primary agent loop, add env vars, verify a first trace lands. Use when the user asks to "set up agenthog", "add agenthog tracing", "instrument with agenthog", "add observability", "wire up tracing", or "add tracing to this app".
Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
Set up the BootLoops protocol skills for this user. Use when the user asks to set up BootLoops, activate or install its skills, or asks what discipline the toolkit ships with. Presents the roster, asks which skills to activate, and installs only what the user chooses.
Create or resume the configured worktree workspace for one task.
Connect the current Agent host to the ArcReel remote MCP service and verify access.
Framework-independent decision process for instrumenting a GenAI/LLM app (Python or TypeScript, any provider/agent SDK) so it emits OTel GenAI semantic-convention (gen_ai.*) spans queryable in Dynatrace. Four steps: detect, instrument, enrich, validate. Decides which approach a given SDK needs; does not replace the concrete per-framework recipes in dynatrace-oss/dynatrace-ai-agent-instrumentation-examples. Trigger: "instrument this GenAI app", "add tracing to this LLM app", "how do I get gen_ai spans into Dynatrace", "onboard this agent app to AI Observability". Do NOT use for analyzing telemetry from an already-instrumented app (use dt-obs-genai) or for languages other than Python/TypeScript.
Sets up code formatting rules and style guidelines in CLAUDE.md
Set up and audit Blender scenes the way studios do - units and real-world scale, collection layout, naming conventions (SM_/SK_/T_/M_), origins, linking vs appending, library overrides, asset libraries and catalogs, collection exporters, orphan/path cleanup. Use when starting a project, organizing a .blend, or before handoff/export.
Use when bootstrapping a team directives repository from scratch, cloning an existing one, pointing to a local path, or checking an existing configuration.
Set up and run experiments in LaunchDarkly. Create experiments with metrics, treatments, and flag config, start iterations to collect data, swap design between iterations, and stop with a winner.
Set up a Paperclip agent and routine that applies a selected code-maintenance skill to a repository and opens pull requests. Use for nightly maintenance bots, scheduled code gardening, or webhook-driven maintenance, using an existing agent or a new hire.
Use when the awwwards MCP server or its skills are invoked for the first time in a session or on a new machine — when no awwwards preferences exist yet, or the user asks to set up, configure, or change awwwards-mcp settings (result density, viewport, live captures, local index, winner watches). First-time onboarding asks the user a short set of preference questions, persists them to ~/.awwwards-mcp/preferences.json, and runs any one-time installs they opt into.