coleam00/skills plugin for Grok Build

Skills (25)

• ablate-ai-layer — Measure whether a repository's AI instructions still earn their place, by running the same real task many times with the layer intact and with it stripped, then grading every rule against what actually changed. Runs both arms itself in thro
• agent-browser — Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Tri
• ast-grep — Guide for writing ast-grep rules to perform structural code search and analysis. Use when users need to search codebases using Abstract Syntax Tree (AST) patterns, find specific code structures, or perform complex code queries that go beyon
• build-dark-factory — Take a PRD and build a dark factory around it - a repository that takes work in as an issue and ships validated code out with nobody at the keyboard - one component at a time, into the user's actual repo. Covers the five components in const
• build-signal-engine — Build a personal signal engine from scratch - a system that reads every source someone cares about each day (changelogs and release notes, communities, feeds, videos, papers), makes a quick decision on every item, lets an LLM read only what
• drive-screen — Take real control of the desktop - list and focus windows, type, paste, click, scroll, and screenshot - on Windows, macOS or Linux, and drive other coding-agent sessions running in terminals. Use when asked to set up the screen or the day,
• hooks-create — Author a working Claude Code hook from a plain-English description of what it should guarantee or do. You describe the behavior ("never let the agent edit my migrations", "don't stop until the tests pass", "log every command"); this skill p
• opportunity-scan — Scan how you actually work with your coding agent and surface what to encode next. Point it at ONE run's artifacts to find what would have prevented a specific failure (the reactive loop — 'that went wrong, what should change in the AI laye
• piv-commit — Creates a new git commit for all uncommitted changes with an atomic, conventionally-tagged message. Use when work is complete and ready to be committed.
• piv-create-pr — Push the current feature branch and open a pull request, ready for review. Use after a ticket's implementation is committed on its own branch — it detects the base branch, pushes, opens the PR with a clear body (summary · what changed · val
• piv-fix-review-findings — Triage code-review findings (manual or AI), fix the ones you choose one at a time with tests, defer/log the rest, then validate — and if the work is on a PR, commit and push so the PR reflects the fixes. Use after a review has produced a li
• piv-implement — Executes an implementation plan task-by-task with validation at every step. Use when you have a completed feature plan and want to implement it in one pass.
• piv-implement-issue — Implement the fix for a GitHub issue from its RCA artifact (created by piv-investigate-issue) — drift-check the plan, branch, implement, add regression tests, and validate. Use after the investigation artifact exists and you're ready to fix
• piv-investigate-issue — Investigate a GitHub issue — fan out parallel exploration, find the root cause (5 Whys, evidence-backed), and write a reviewable RCA artifact (then post a summary to the issue). The investigate step before piv-implement-issue. Use to diagno
• piv-plan-implementation — Creates a comprehensive, context-rich implementation plan through deep codebase analysis, a short clarifying interview, and external research. Accepts a tracker ticket (a Jira/Linear/GitHub key or URL, fetched from the tracker) or a free-fo
• piv-review-changes — Performs a technical code review of recently changed files for bugs, security issues, and standards compliance, then writes a report. Use before committing, as a pre-commit quality gate.
• piv-review-pr — Full pull-request review — fetch the PR, run the project's validation, review the diff with fresh eyes (dispatching the code-reviewer agent), categorize issues by severity, post the review to GitHub (approve / request-changes / comment), an
• piv-run-full-loop — Autonomously develops a complete feature from priming through planning, execution, and commit by chaining the four core PIV-loop skills. Use when you want a full hands-off feature build from a single description.
• piv-slice-epic — Slice an epic (with its architecture decisions) into PIV-sized tickets with a dependency graph, then create them in your tracker (Jira via the Atlassian MCP, or GitHub/Linear/local). Accepts the epic and its architecture as one doc or as an
• piv-validate — Runs this project's full validation suite — tests, type checks, and linting across every part of the stack — then reports overall health. Use before committing, before opening a PR, or after finishing a chunk of work to confirm zero regress
• plan-architecture — Interactively explore HOW to approach an intent (a PRD, epic, brief, or free-form idea) and decide the high-level architecture — the approach, stack, libraries, data shape, and risks the intent left open. A working session with a CTO/staff-
• plan-create-prd — Interactive, problem-first PRD generator — interviews the user to surface the thesis (the problem, and WHY build it) and a falsifiable hypothesis, then writes a focused PRODUCT-level PRD (problem · evidence · hypothesis · users · MVP · succ
• plan-create-stories — Decomposes a PRD into well-formed, engineer-ready tickets — Jira issues or GitHub issues. Use after a PRD exists, to turn its phases and user stories into a structured backlog. Works for a new codebase (MVP scope) or an existing one (epic s
• prime-backend — Primes the agent with focused understanding of the backend portion of the codebase — API routes, services, data models, and database layer — without loading unrelated frontend code. Use at the start of a session when the work is scoped to A
• prime-codebase — Primes the agent with deep codebase understanding by analyzing structure, documentation, and key files. Use when starting work on a codebase, at the beginning of a session, or when you need a fast orientation before planning or implementing