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SkillsMP has collected 31 skills from coleam00/skills. Open a skill to review its source and details.
Showing 31 of 31 collected skills.
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 picks the right…
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 construction order - the…
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 layer?'), or at a…
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.
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 diagnose a bug/issue…
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), and save a report.…
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 · success metrics ·…
Set up your project's global rules, a lean and well-structured root CLAUDE.md (plus a starter .claude/), following the course methodology. Greenfield: pass your PRD and/or architecture-spec path and it derives rules from your engineering decisions (a PRD…
Author a new Claude Code skill the house way, or refactor a fat skill into a lean SKILL.md + references/. Use when you want to "create a skill", "write a new skill", "turn a prompt or command into a skill", "split a skill into references", "trim a SKILL.md",…
Integrate any number of feature branches from parallel worktrees through one safe integration branch, validating after each merge and running the project's full check suite before touching the main line. Use when parallel worktree development is done and the…
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-form feature request.…
Audit any second brain, notes folder, or agent memory for facts that have quietly stopped being true, then fix the worst one so it stops recurring. Works on a wiki, a single notes file, daily notes, or a non-markdown tool, and adapts the fix to whichever it…
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 throwaway git worktrees…
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.
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 · validation status),…
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 list of issues or a…
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 the issue.
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.
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.
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 epic plus a…
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 regressions.
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-engineer advisor…
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 scope).
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 API endpoints,…
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. Optionally pulls…
Primes the agent with focused understanding of the frontend portion of the codebase — components, routing, state management, and styling — without loading unrelated backend code. Use at the start of a session when the work is scoped to UI or client-side…
Check whether your rules file (CLAUDE.md or AGENTS.md) still matches the codebase after recent changes — run before a merge, or fold into your code-review pass. Reports stale/now-false rules, drifted architecture-map entries, and any new invariant worth…
Sets up and starts the AI Tutor project locally (environment file, dependencies, database, migrations, and dev server). Use when standing up the AI Tutor for the first time on a new machine or after a fresh clone. This is sample-project specific; adapt it…
Performs a meta-level review of how well an implementation followed its plan, classifying divergences and recommending AI-Layer improvements. Use after an execution report exists to find bugs in the process, not the code.
Generates a structured implementation report reflecting on a just-completed feature — what was done, divergences, challenges. Use right after finishing an implementation, as the input to a system review.
Create one or more git worktrees for parallel development, each on its own branch with gitignored config copied in, dependencies installed, and a health check, by fanning out a setup subagent per worktree. Use when starting isolated parallel work, running…