Custom research, planning, and implementation workflows with agent-awareness and platform debugging orchestration (GCP, Kubernetes, Linear)
ALWAYS check this skill before using grep, glob, Task tool, or doing any codebase exploration. Guides you to use specialized agents that are more efficient than basic tools.
Use BEFORE reading multiple files to understand code. Reminds you to use codebase-analyzer agent instead of manual file reading.
Use BEFORE running grep or glob commands. Reminds you to use codebase-locator agent instead of basic file search tools.
Use BEFORE using the Task tool. Ensures you select the correct specialized subagent_type instead of generic agents.
Use when encountering errors or bugs to follow a systematic debugging process instead of jumping to conclusions.
Use during planning to discover and document available project commands (make targets, npm scripts, etc.) for success criteria.
Use during planning to discover and document test patterns and conventions for writing consistent tests.
Use when writing tests to ensure they follow project conventions. References patterns from thoughts/notes/testing.md.
ALWAYS check before using gcloud commands. Guide for GCP-related skills and tools.
Query GCP Cloud Logging for errors, service logs, and request traces. Use when investigating GCP-hosted services.
ALWAYS check before using kubectl commands. Guide for Kubernetes-related skills.
Launch ephemeral debug container in running pod for interactive debugging. Use when you need to debug a pod without restarting it.
Query Kubernetes resources (pods, deployments, services, events). Use when checking cluster state and resource status.
ALWAYS check before working with Linear issues. Guide for Linear-related skills for ticket management and debugging workflows.
Fetch and view Linear issues/tickets. List, search, read issue details, status, comments. Use when investigating tickets or gathering debugging context.
Use when creating implementation plans to research codebase patterns and gather context for planning.
Use when conducting codebase research to orchestrate specialized agents in parallel for comprehensive investigation.
Use after implementing changes to run verification commands and ensure tests pass, code builds, and functionality works.
Use when creating git commits to ensure consistent, clear commit messages following conventional commits format.
Use when creating implementation plans to generate properly structured plans with phases, success criteria, and project references.
Use when creating pull requests to write clear, structured PR descriptions that help reviewers understand changes.
Use when documenting research findings to create properly structured research documents with frontmatter, sections, and file references.