Write, refactor, and ship code with an agent that knows your stack.
Most artifacts in the catalog live here: tools that read a codebase, follow its conventions, and make changes you would not be embarrassed to review. Expect language-specific helpers, refactoring workflows, spec-driven development harnesses, and framework-aware assistants for stacks like React, Next.js, Python, Rust, and Go. If you want your agent to stop writing generic code that ignores how your project actually works, start here.
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Animation and motion design patterns using Motion library (formerly Framer Motion) and View Transitions API. Use when implementing component animations, page transitions, micro-interactions, gesture-driven UIs, or ensuring motion accessibility with prefers-reduced-motion.
Read-only MCP server for the OrchestKit docs: full-text search + Markdown fetch. No auth.
Reverse engineer clean behavioral specs from any codebase
Intent-classified router — the front door to OrchestKit and the DEFAULT entry point for any goal-shaped request. Takes a plain-English goal, classifies it into one intent category, and routes to the right specialist skill (/ork:fix-issue, /ork:cover, /ork:brainstorm, /ork:implement, /ork:review-pr, /ork:verify, a /goal optimization loop, or the skill-evolution gate). A goal that maps unambiguously to one skill short-circuits straight to it — routing is never overhead, so use it even when you think you know the target skill. Skip only when already executing inside another skill (no recursion). Triggers on: auto, do this, figure out, just make, get it to, I want, help me, fix, build, improve, any goal description.
Async job processing patterns for background tasks, Celery workflows, task scheduling, retry strategies, and distributed task execution. Use when implementing background job processing, task queues, or scheduled task systems.
AI efficiency framework. Smarter output, intelligent routing, persistent memory, context discipline, project workflows. One install. Zero config. It just fucking works.
Business case analysis with ROI, NPV, IRR, payback period, and TCO calculations for investment decisions. Use when building financial justification, cost-benefit analysis, build-vs-buy comparisons, or sensitivity analysis.
The Complete AI Development Toolkit — 114 skills, 37 agents, 216 hooks for full-stack development.
One-command installer for IJFW -- the AI efficiency layer. One install, every AI coding agent, zero config.
Accessibility patterns for WCAG 2.2 compliance, keyboard focus management, React Aria component patterns, cognitive inclusion, native HTML-first philosophy, and user preference honoring. Use when implementing screen reader support, keyboard navigation, ARIA patterns, focus traps, accessible component libraries, reduced motion, or cognitive accessibility.
Audits all OrchestKit skills for quality, completeness, and compliance with authoring standards. Use when checking skill health, before releases, or after bulk skill edits to surface SKILL.md files that are too long, have missing frontmatter, lack rules/references, or are unregistered in manifests.
Diagnose IJFW integration health per platform. Trigger: 'doctor', 'check setup', /doctor
ASCII diagram patterns for architecture, workflows, file trees, and data visualizations. Use when creating terminal-rendered diagrams, box-drawing layouts, progress bars, swimlanes, or blast radius visualizations.
Assesses and rates quality 0-10 across multiple dimensions (correctness, maintainability, security, performance, testability, simplicity) with pros/cons analysis. Compares against project conventions and prior decisions from memory. Produces structured evaluation reports with actionable improvement suggestions. Use when evaluating code, designs, architectures, or comparing alternative approaches.
Cross-platform persistent memory server for IJFW. 14 MCP tools (memory + admin/update + brain). Works with 15 platforms: 14 via MCP (Claude Code, Codex, Gemini CLI, Cursor, Windsurf, Copilot, Hermes, Wayland, OpenCode, QwenCode, Cline, KimiCode, OpenClaw, Antigravity) plus Aider via the rules-only tier.
Rate-limit-resilient pipeline with checkpoint/resume for long multi-phase sessions. Saves progress to .claude/pipeline-state.json after each phase. Use when starting a complex multi-phase task that risks hitting rate limits, when resuming an interrupted session, or when orchestrating work spanning commits, GitHub issues, and large file changes.
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for org-wide CI sweeps (that's /status) or for app-level test failures (the playbook is CI-infra-specific).
Use when the user says: 'ijfw status', 'show me the system state', 'what is ijfw doing', or to see the at-a-glance routing / memory / activity banner.
Audits OrchestKit sub-agent activation from real spawn telemetry — computes the generic-vs-specialist spawn split, flags dormant agents (never fired), and classifies each as fires/mis-triggered/niche. The agent-side analogue of audit-skills. Use when specialized agents feel under-used, before pruning the catalog, or after wiring new agent spawn paths.
AI-assisted UI generation patterns for json-render, v0.app, Google Stitch, Bolt Cloud, and Cursor workflows. Covers prompt engineering for component and full-stack app generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
Analyzes the current implementation run — evaluates schema effectiveness, delegation alignment, note quality, and plan-to-execution fit. Captures cross-session trends and proposes improvements when patterns repeat. Use after implementation runs, or when user says 'retrospective', 'session review', 'what did we learn', 'analyze this run', 'how did that go', 'evaluate our process', 'wrap up', 'end of session review'. Also use when the output style's retrospective nudge fires after complete_tree.
Chain patterns for CC 2.1.71 pipelines — MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building multi-phase pipeline skills. Loaded via skills: field by pipeline skills (fix-issue, implement, brainstorm, verify). Not user-invocable.
Guides the full lifecycle of a feature-implementation tagged MCP item (the feature container) — from queue through review. Creates or resumes the feature container, fills gate-enforced notes at each phase (requirements, design, implementation-notes, test-results), dispatches implementation subagents, and advances through queue, work, and review to terminal. Use when the user says: implement a feature, start a new feature, feature workflow, resume feature work, guide feature lifecycle, or references a feature-implementation item UUID.
Specification quality framework for planning. Defines the minimum bar for what a plan must address — alternatives, non-goals, blast radius, risk flags, and test strategy. Referenced by schema guidance fields during queue-phase note filling. Use when filling requirements or design notes for any MCP work item.
Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, edge, model migration, version upgrades, and SDK usage
Assessment of plugin skill and hook changes needed after MCP or config changes. Evaluates skill references, hook context, config-format docs, and output style references. Invoked via skillPointer when filling plugin-impact notes.
End-to-end release automation — reads commits since last tag, infers semver bump, drafts changelog, creates release PR, merges it, waits for CI green, tags, and monitors the Docker build to completion. Use when the user says: prepare release, cut a release, bump version, create release PR, ship a new version, tag a release, deploy new version, or when all feature PRs are merged and it is time to release.
A personal AI tutor based on Bloom's 2-sigma research: it generates a structured syllabus, teaches one adaptive lesson at a time, and tailors each next lesson to the learner's highlights and feedback. Bundles the bloom-tutor tutoring skill plus six learn-* learning-method skills.
Performance impact assessment for items with the needs-perf-review trait. Evaluates hot paths, query patterns, and measurement plans. Invoked via skillPointer when filling performance-baseline notes.
Claude Code integration for MCP Task Orchestrator — schema-aware context, note-driven workflow
Summarize the architecture of code generated by a single retort run. Produces module-level structure, interfaces, and control flow in a form suitable for cross-run comparison — not a full codebase-summary.
Review quality framework for the work-to-review transition gate. Guides verification of plan alignment, test quality, and code simplification before marking implementation complete. Referenced by schema guidance fields during review-phase note filling. Use when filling review-checklist notes or when asked to review completed implementation work.
SQLite migration assessment for items with the needs-migration-review trait. Evaluates schema changes, table recreation patterns, data migration strategy, and Flyway migration correctness. Invoked via skillPointer when filling migration-assessment notes.
MCP server and OpenAPI-backed mobile companion for controlling Antigravity IDE sessions
End-to-end workflow for taking MCP work items from backlog to merged PR. Handles git branching, schema-driven planning, implementation, independent review, and PR creation. Composes spec-quality, review-quality, and schema-workflow skills into a single pipeline. Use when a user says "implement this", "work on this item", "fix these bugs", "pick up the next task", "create a PR for this", "go through the backlog", or references specific MCP item IDs for implementation.
Blueprint-driven Claude Code autopilot. Smart preparation over endless iterations - AI analyzes patterns, creates solid implementation plans, delivers working code in 15 minutes.
Simplify and refactor code while preserving functionality and library constraints.
Analyze project structure, write the thick requirements doc (.claude/docs/DESIGN.md), populate the thin "Repository Identity" pointer in CLAUDE.md (Zone B), and mirror identity into AGENTS.md.
cmux for Windows — run multiple AI CLI agents (Claude Code, Codex, Gemini) side-by-side with an MCP bridge and browser automation
Create a detailed implementation plan for a feature or task. Use when user wants to plan before coding.
Implement features using Test-Driven Development (TDD) with Red-Green-Refactor cycle.
Model Context Protocol (MCP) server for OpenClaw AI assistant integration
Domscribe is a pixel-to-code development tool that maps running UI elements to their exact source locations, capturing runtime context (props, state, DOM) for handoff to coding agents via MCP.
Antigravity CLI plugin for safe Google Apps Script development via ggsrun MCP and sandbox guardrails.
Turns product or tech specs into concrete Notion tasks that Claude code can implement. Breaks down spec pages into detailed implementation plans with clear tasks, acceptance criteria, and progress tracking to guide development from requirements to completion.
Local-first AI identity for MCP coding tools. Lessons, decisions, and context you control.
OpenAI Codex CLI integration for AgenticMail — surfaces every AgenticMail agent as a native Codex subagent and wires the dispatcher daemon to the Codex SDK
MCP server for AgenticMail — give any AI client real email, SMS, and phone call-control capabilities