Claude Skills by v1truv1us

Review recently changed files for code reuse, quality, and efficiency issues, then fix them. Alias for code-simplification skill with multi-agent review additions.

Contract-first design, Hyrum's Law, One-Version Rule, error semantics, boundary validation. Use when designing APIs, module boundaries, or public interfaces.

Chrome DevTools for live runtime data - DOM inspection, console logs, network traces, performance profiling. Use when building or debugging anything that runs in a browser.

Run the full repository compatibility pass: scanner score, startup path, validation loop, and docs reliability.

Run compile and type-check commands and report failures

Design CI/CD pipelines, quality gates, and iterate on failing PR checks until green. Use when setting up pipelines or fixing CI on a branch.

Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.

Multi-axis code review with optional strict maintainability mode. Use before merging any change—human, agent, or automation output.

Simplifies code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be.

Multi-phase research orchestration for thorough codebase, documentation, and external knowledge investigation. Invoked by /ai-eng/research command. Use when conducting deep analysis, exploring codebases, investigating patterns, or synthesizing findings from multiple sources.

Enhance any content type using research-backed techniques. Optimize AI prompts with step-by-step approval, improve code quality, refine database queries, enhance documentation, optimize commit messages, and improve communication. Wraps incentive-prompting skill with content-type detection.

Context window management for AI agents. Optimize context usage, prevent overflow, and ensure critical information is always available. Use when working with large codebases or long sessions.

Feed agents the right information at the right time. Use when starting a session, switching tasks, or when output quality drops due to missing or stale context.

Instinct-based learning with confidence scoring, AGENTS.md memory updates, and evolution into durable skills. Use when extracting patterns from completed work or mining transcript deltas for reusable preferences.

Build or adapt a local harness to drive, inspect, and profile an interactive CLI or TUI without external services. Use for CLI UX checks, startup regressions, memory leaks, hangs, prompt flows, or terminal demos.

Build or adapt a local browser/CDP harness to drive and inspect a web, IDE, or Electron UI. Use for local UI verification, screenshots, accessibility snapshots, perf profiles, visual diffs, or reproducing UI bugs.

Deploy applications to Coolify self-hosting platform. Use when deploying to Coolify, configuring build settings, setting environment variables, managing health checks, or performing rollbacks.

Build a personalized learning roadmap with milestones and practice checkpoints

Guide building apps, scripts, CI pipelines, and automations with the Cursor TypeScript SDK (`@cursor/sdk`). Use when integrating `Agent.create`, `Agent.prompt`, `Agent.resume`, streaming, MCP servers, local vs cloud runtime, errors, or porting REST `/v1/agents` calls to the SDK. Prefer this skill over memory—the SDK surface evolves and references here are the source of truth.

Guides systematic root-cause debugging. Use when tests fail, builds break, behavior does not match expectations, or any unexpected error appears.

Build and reason about import graphs, call graphs, schema graphs, and service dependency graphs. Use when tracing paths, finding god nodes, surfacing cycles, or answering architecture questions about how parts connect.

Code-as-liability mindset, compulsory vs advisory deprecation, migration patterns, zombie code removal. Use when removing old systems, migrating users, or sunsetting features.

Structured document review for structure, clarity, and technical accuracy. Use for \"review this doc\", feedback, critique, or /doc-review.

Render a documentation-style Cursor Canvas that organizes architecture notes, API references, walkthroughs, and how-tos into a navigable layout with sections, tables of contents, and cross-references. Use when the user asks for a docs canvas, documentation overview, architecture walkthrough, API reference page, or wants to render structured documentation as an interactive canvas.

Architecture Decision Records, API docs, inline documentation standards. Use when making architectural decisions, changing APIs, or shipping features. Document the why, not the what.

Agent evaluation framework. Measure agent performance, identify weaknesses, and track improvement over time. Use when assessing agent quality, comparing approaches, or validating changes.

Find failing PR checks, inspect logs or external check links, and apply focused fixes

Resolve merge conflicts non-interactively, validate build and tests, and finalize conflict resolution

Component architecture, design systems, state management, responsive design, WCAG 2.1 AA accessibility. Use when building or modifying user-facing interfaces.

Fetch and summarize review comments from the active pull request

Trunk-based development, atomic commits, change sizing (~100 lines), commit-as-save-point pattern. Use when making any code change.

Manage Git worktrees for parallel development. Use when creating isolated workspaces for parallel feature work, running multiple Claude sessions simultaneously, or managing concurrent development tasks.

Relationship-aware retrieval using graph traversal, entity anchors, community expansion, and hybrid vector plus graph search. Use when chunk similarity alone misses paths, entities, or subsystem context.

Knowledge graph development for LLM applications. Graph storage selection, graph algorithms, extraction from documents/code/websites, entity extraction, Graph RAG, and visualization. Use when building knowledge graphs, graph databases, or LLM graph applications.

Structured divergent/convergent thinking to turn vague ideas into concrete proposals. Use when you have a rough concept that needs exploration before committing to a spec.

Research-backed prompting techniques for improved AI response quality (+45-115% improvement). Use when optimizing prompts, enhancing agent instructions, or when maximum response quality is critical. Invoked by /ai-eng/optimize command. Includes expert persona, stakes language, step-by-step reasoning, challenge framing, and self-evaluation techniques.

Delivers changes in thin vertical slices. Use when implementing any feature or refactor that touches more than one file or feels too large to land safely in one pass.

Build a static-first knowledge architecture using file-backed domain maps, rules, hypotheses, and durable references. Use for knowledge architecture, learning systems, decision context, and long-lived team memory without runtime memory tooling.

Document solved problems to build cumulative team knowledge. Systematically capture solutions with context, code examples, gotchas, and related links. Use after completing workflows to ensure learnings compound for future team members.

Monitor PR checks and fix failures until green. Uses gh pr checks as the source of truth for PR-attached checks.

Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for \"make this easy to review\", \"tidy this PR\", \"clean up commits\", or \"annotate the diff\".

Recursively initialize AGENTS.md in monorepo subdirectories with smart detection. Creates hierarchical agent context files with proper linking to root CLAUDE.md and parent AGENTS.md. Use for setting up multi-package projects, microservices, or any project with important subdirectories that need AI agent guidance.

Daily briefing synthesizing calendar, tasks, and priorities. Use for \"morning brief\", \"daily briefing\", \"start my day\", or /morning-brief.

Normalize mixed inputs like code, docs, PDFs, screenshots, diagrams, audio, and transcripts into a structured corpus. Use when the task depends on combining multiple artifact types before analysis or retrieval.

Create a fresh branch, complete work, and open a pull request

Publish npm packages via GitHub Actions with OIDC trusted publishing and provenance. Use when setting up automated npm publishes, debugging ENEEDAUTH/E404 errors, or configuring provenance attestations.

Use only when the user explicitly types `/orchestrate <goal>` to decompose a large task, spawn a tree of parallel cloud-agent workers/subplanners/verifiers via the Cursor SDK, and collect structured handoffs; do not invoke autonomously.

Measure-first approach for Core Web Vitals targets, profiling workflows, bundle analysis, and anti-pattern detection. Use when performance requirements exist or you suspect regressions.

Decompose specs into small, verifiable tasks with acceptance criteria and dependency ordering. Use when you have a spec and need implementable units.

This skill should be used when creating extensions for Claude Code or OpenCode, including plugins, commands, agents, skills, and custom tools. Covers both platforms with format specifications, best practices, and the ai-eng-system build system.