codeaholicguy
12 verified skills13,961 total stars
dev-lifecycle
AI DevKit · Structured SDLC workflow with 8 phases — requirements, design review, planning, implementation, testing, and code review. Use when the user wants to build a feature end-to-end, or run any individual phase (new requirement, review requirements, review design, execute plan, update planning, check implementation, write tests, code review).
development1,226
document-code
AI DevKit · Document a code entry point with structured analysis, dependency mapping, and saved knowledge docs. Use when users ask to document, understand, or map code for a module, file, folder, function, or API.
development1,190
verify
AI DevKit · Enforce evidence-based completion claims — require fresh command output before reporting success. Use when completing any task, fixing a bug, finishing a phase, running tests, building, deploying, or making any "it works" claim.
development1,190
technical-writer
AI DevKit · Review and improve documentation for novice users. Use when users ask to review docs, improve documentation, audit README files, evaluate API docs, review guides, or improve technical writing.
development1,190
simplify-implementation
AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical debt, or make code easier to understand.
development1,190
security-review
AI DevKit · Review code, skills, and prompts for security vulnerabilities — OWASP Top 10, prompt injection, business logic flaws, and insecure defaults. Use when reviewing PRs, auditing modules, reviewing AI skills/prompts, or preparing for release.
development1,190
memory
AI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.
tools1,190
structured-debug
AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).
development1,190
tdd
AI DevKit · Test-driven development — write a failing test before writing production code. Use when implementing new functionality, adding behavior, or fixing bugs during active development.
development1,190
agent-orchestration
AI DevKit · Proactively orchestrate running AI agents — scan statuses, assess progress, send next instructions, and coordinate multi-agent workflows. Use when users ask to manage agents, orchestrate work across agents, or check on agent progress.
development1,187
capture-knowledge
Capture structured knowledge about a code entry point and save it to the knowledge docs. Use when users ask to document, understand, or map code for a module, file, folder, function, or API.
development1,014
debug
Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).
development1,014