Build AI-powered features with disciplined prompt engineering, evaluation, and observability. Use when integrating LLMs, building agents, or shipping AI capabilities.
EnglishCreate, critique, and operationalize engineering strategy documents using diagnosis, tradeoff exploration, guiding policy, coherent actions, and operating cadence. Use when an engineering leader needs strategy for a team, platform, architecture, migration, reliability program, or multi-quarter technical investment.
EnglishRun engineering leadership reviews across strategy, delivery, quality, architecture, launch readiness, security risk, and performance health.
EnglishMake ML experiments reproducible and comparable by tracking hyperparameters, metrics, artifacts, and environments. Use when training models, tuning hyperparameters, or promoting models to production.
EnglishInstrument code with structured logs, metrics, and distributed traces. Use when adding observability to services, debugging production issues, or setting up monitoring.
EnglishRamp up quickly on an unfamiliar codebase by reading strategically, mapping invariants, and making safe first changes. Use when joining a project, reviewing a legacy system, or orienting in a large monorepo.
EnglishIncludes AI Feature Development, Crafting Engineering Strategy, Leadership Review, and other workflows.
Supported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
AI Feature Development
Build AI-powered features with disciplined prompt engineering, evaluation, and observability. Use when integrating LLMs, building agents, or shipping AI capabilities.
Crafting Engineering Strategy
Create, critique, and operationalize engineering strategy documents using diagnosis, tradeoff exploration, guiding policy, coherent actions, and operating cadence. Use when an engineering leader needs strategy for a team, platform, architecture, migration, reliability program, or multi-quarter technical investment.
Leadership Review
Run engineering leadership reviews across strategy, delivery, quality, architecture, launch readiness, security risk, and performance health.
Ml Experiment Tracking
Make ML experiments reproducible and comparable by tracking hyperparameters, metrics, artifacts, and environments. Use when training models, tuning hyperparameters, or promoting models to production.
Observability and Monitoring
Instrument code with structured logs, metrics, and distributed traces. Use when adding observability to services, debugging production issues, or setting up monitoring.
Onboarding and Archaeology
Ramp up quickly on an unfamiliar codebase by reading strategically, mapping invariants, and making safe first changes. Use when joining a project, reviewing a legacy system, or orienting in a large monorepo.
Quick start
- Choose your skills. Select individual skills above, or choose the entire pack.
- Copy the install prompt. Use Copy install prompt above the list.
- Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.
Try it with your agent
After installation, start with a request like:
Use the AI Feature Development skill to help with my task.
Ask me for the context you need before getting started.Requirements & license
- A coding agent that can access your project files and install skills.
- Your agent checks each skill’s instructions, dependencies, and permissions during setup.
- License details are not provided in these listings. Check the author’s terms before using the skills.