v1truv1us-ai-eng-system

Plugin v1truv1us-ai-eng-system from marketplace cascade-code-devops-misc-2 in joshuarweaver/cascade-code-devops-misc-2. Commands read from the repo's manifest — 1 month ago.

Skills (128)

• simplify

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

• api-and-interface-design

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

• browser-testing-with-devtools

  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.

• check-agent-compatibility

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

• check-compiler-errors

  Run compile and type-check commands and report failures

• ci-cd-and-automation

  Shift Left, Faster is Safer, feature flags, quality gate pipelines, failure feedback loops. Use when setting up or modifying build and deploy pipelines.

• cli-for-agents

  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, t

• code-review-and-quality

  Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human.

• code-simplification

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

• comprehensive-research

  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.

• content-optimization

  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-budget

  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.

• context-engineering

  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.

• continuous-learning-v2

  Instinct-based learning system with confidence scoring, import/export, and evolution into skills. The system learns patterns from sessions and promotes high-confidence instincts into durable skills. Use when extracting patterns from completed work.

• control-cli

  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.

• control-ui

  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.

• coolify-deploy

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

• create-learning-path

  Build a personalized learning roadmap with milestones and practice checkpoints

• cursor-sdk

  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 ov

• debugging-and-error-recovery

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

• dependency-graph-analysis

  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.

• deprecation-and-migration

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

• doc-review

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

• docs-canvas

  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 ref

• documentation-and-adrs

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

• eval-harness

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

• fix-merge-conflicts

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

• frontend-ui-engineering

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

• get-pr-comments

  Fetch and summarize review comments from the active pull request

• git-workflow-and-versioning

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

• git-worktree

  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.

• graph-rag

  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.

• graphify

  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.

• idea-refine

  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.

• incentive-prompting

  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

• incremental-implementation

  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.

• knowledge-architecture

  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.

• knowledge-capture

  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.

• make-pr-easy-to-review

  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\".

• monorepo-initialization

  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 a

• morning-brief

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

• multimodal-corpus-ingestion

  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.

• new-branch-and-pr

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

• npm-trusted-publishing

  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.

• orchestrate

  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.

• performance-optimization

  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.

• planning-and-task-breakdown

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

• plugin-dev

  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.

• pr-review-canvas

  Generate an interactive PR review walkthrough as an HTML page. Fetches PR data via gh API, categorizes files into core vs mechanical changes, adds reviewer annotations, and renders diffs with moved-code detection. Use when the user pastes a GitHub PR URL and asks for a review, walkthrough, or summar

• prompt-engineering

  Comprehensive prompt engineering for coding agents covering structured instruction design, few-shot prompting, chain-of-thought, decomposition, agent workflow patterns, and reliability techniques for multi-step pipelines.

• prompt-refinement

  Transform prompts into structured TCRO format with phase-specific clarification. Automatically invoked by /ai-eng/research, /ai-eng/plan, /ai-eng/work, and /ai-eng/specify commands. Use when refining vague prompts, structuring requirements, or enhancing user input quality before execution.

• architect

  Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in. Use for /architect, 'architect this', 'design this', or non-trivial work where jumping to code would lock in the wrong shape.

• arena

  Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for /arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.

• automate-me

  Use for \"automate me\", \"create/update/refresh my -mode skill\", \"turn/capture my preferences or working style into a skill\", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill via create-skill + unslop, optionally pulling fresh evidence from recent transcri

• how

  Use for \"how does X work\", code walkthroughs before changing something, and placement / ownership / layering questions (\"where should this live\", \"which package owns this\", \"is this the right layer\"). Explains subsystem architecture, runtime flow, onboarding mental models. Can critique archi

• interrogate

  Use for \"interrogate\", \"adversarial review\", \"multi-model review\", \"challenge this\", \"stress test this code\", \"find blind spots\", or \"tear this apart\". Four LLM reviewers challenge changes from independent angles.

• poteto-mode

  poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.

• principle-boundary-discipline

  Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.

• principle-encode-lessons-in-structure

  Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.

• principle-exhaust-the-design-space

  Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.

• principle-experience-first

  Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.

• principle-fix-root-causes

  Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.

• principle-foundational-thinking

  Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.

• principle-guard-the-context-window

  Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.

• principle-laziness-protocol

  Apply when refactoring, evaluating diff size, or tempted to add abstractions, layers, or signal threading. Bias toward deletion and the smallest change that solves the problem.

• principle-make-operations-idempotent

  Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

• principle-migrate-callers-then-delete-legacy-apis

  Apply when introducing a new internal API while old callers still exist. Migrate callers and delete the old API in the same wave instead of preserving compatibility layers.

• principle-minimize-reader-load

  Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.

• principle-never-block-on-the-human

  Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.

• principle-outcome-oriented-execution

  Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.

• principle-prove-it-works

  Apply after completing a task, before declaring done. Verify against the real artifact (run the feature, read the actual value, inspect the diff), not a proxy, self-report, or 'it compiles.

• principle-redesign-from-first-principles

  Apply when integrating a new requirement into an existing design. Redesign as if the requirement had been a foundational assumption from day one, instead of bolting it on.

• principle-separate-before-serializing-shared-state

  Apply when concurrent actors might write to the same file, branch, key, or state object. Eliminate the sharing first; serialize structurally only when one shared writer is a real invariant.

• principle-subtract-before-you-add

  Apply when sequencing an addition, refactor, or rewrite. Remove dead weight, redundant validators, and stub references first, then build on the simpler base.

• principle-type-system-discipline

  Apply when designing types, reviewing a function signature, or writing code in any statically-typed language. Make illegal states unrepresentable, brand semantic primitives, parse external data at boundaries, refuse to lie to the compiler, exhaust variants, derive from authoritative schemas.

• reflect

  Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.

• tdd

  Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.

• typescript-best-practices

  TypeScript best practices. Use when reading or editing any .ts or .tsx file.

• unslop

  Cut AI tells from any writing. Must always apply.

• why

  Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, prod

• repurpose
• research-deep
• run-learning-retrospective
• run-smoke-tests
• security-and-hardening
• shipping-and-launch
• source-driven-development
• spec-driven-development
• test-driven-development
• text-cleanup
• using-agent-skills
• verification-loop
• weekly-review
• what-did-i-get-done
• workflow-from-chats
• ralph-wiggum
• auto-research
• wiki-research-engineering
• wiki-research-personal
• wiki-research-research
• seo-audit
• slack
• create-goal
• dynamic-router
• grill-me
• grill-with-docs
• storm-research
• sync-skill-taxonomy
• cross-repo-refactor
• docker
• fix-ci
• github
• k8s
• loop-on-ci
• monitoring
• sentry
• continuous-learning
• dreaming-consolidator
• teach
• agents-sdk-dev
• gemini-agent-sdk
• playwright
• repo-audit
• test-fix-loop
• thermo-nuclear-architecture-review
• thermo-nuclear-performance-review
• xcodebuild
• investigation-loop

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