cognitive-baseline-eval
Execute the Joseph Cognitive Baseline v2.1 (JC B-v2.1) 5-Scenario Test Suite to quantify AI alignment, friction maintenance, and protocol adherence.
Discover databases cicd skills, compare source repositories and read the instructions for each workflow.
Execute the Joseph Cognitive Baseline v2.1 (JC B-v2.1) 5-Scenario Test Suite to quantify AI alignment, friction maintenance, and protocol adherence.
Execute graceful degradation when system constraints exceeded.
Activate emergency failsafe chassis when primary systems fail.
Execute graceful reintegration after failsafe activation.
Integrate coverport into Go repositories with Tekton pipelines to enable e2e test coverage collection and upload to Codecov. Use this skill when users ask to integrate coverport, add e2e coverage tracking, or s...
Project-specific patterns, conventions, and learnings for docker-containers. Triggers: "project patterns", "how does this project", "project conventions", "local setup", "build order", "test setup", "project-sp...
Create an opence plan and scaffold change artifacts.
Guides the creation of high-quality Pull Requests that adhere to repository standards, covering template discovery, drafting descriptions, and executing PR creation commands.
Kubernetes deployment patterns and best practices. Use when creating Kubernetes manifests, Helm charts, configuring pods, services, deployments, or troubleshooting K8s clusters.
Terraform infrastructure as code patterns and best practices. Use when writing Terraform configurations, creating modules, managing state, or designing IaC architectures.
Design and implement multi-step automation workflows
Build intent routers for agent task distribution
Best practices for containerizing applications with Docker.
Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically, executes tasks in batches, reports for review between batches...
Use when completing tasks, implementing major features, or before merging to verify work meets requirements - dispatches superpowers:code-reviewer subagent to review implementation against plan or requirements...
Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and ve...
Use when creating new skills, editing existing skills, or verifying skills work before deployment - applies TDD to process documentation by testing with subagents before writing, iterating until bulletproof aga...
Reviews the git changes, identifies critical and high-priority issues, generates review summaries, and collects metrics data for local use. Use this when users need to code review or analyzing code changes for...
Autonomously run quality checks (detekt, Gradle tests) to establish baseline or detect regressions. Supports three modes (capture, compare, auto) for comprehensive regression detection. Triggers before starting...
Use when executing /code:review-uncommited, /code:review-unpushed, or /code:review-pr commands. Triggers: code review request, PR review, uncommited changes review. Defines 12 parallel review agents covering se...
This skill should be used when the user asks about "deploying", "production", "Agent Engine", "Vertex AI", "Cloud Run", "GKE", "Kubernetes", "hosting", "scaling", "guardrails", "safety", "content filtering", "i...
Sets up and installs the AI Software Architect framework in a NEW project for the FIRST time. Use when the user requests "Setup .architecture", "Setup ai-software-architect", "Initialize architecture framework"...
Scans repository for security issues and automatically remediates them. Use when the user asks to "clean up security issues", "fix security problems", "remove sensitive data", "sanitise the repo", or "/repo-sec...
Checks documentation consistency across the repository. Use when user asks to "check consistency", "are the documents consistent", "is everything aligned", "verify documentation", or "/repo-consistency".
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.