Plugins

Default Define + Plan skills: interview-me and idea-refine (Define-phase intent extraction and idea refinement, forked from addyosmani/agent-skills), brainstorming, written implementation plans, and lavish — a bridge plus /lavish command for the kunchenguid/lavish-axi CLI that renders agent output (plans, tables, diagrams, diffs, reports) as reviewable HTML artifacts the user annotates in the browser (installed on demand via /lavish-engine). Depends on pro-execution for worktree and subagent execution handoff.

Quality gate skills: requesting + receiving code review, verification-before-completion, validation handoff. Enforces doc freshness before git push and blocks plan saves outside the project directory.

Deep web research engine for any topic. /research <question> runs an adaptive intake interview, then decomposes into angles, fans out research subagents over a free-first retrieval ladder (Serper -> Jina/Firecrawl -> agent-browser), verifies citations, and synthesizes a cited report. /lead-research <company|domain|ICP> is the lead/account specialization: same engine plus ICP scoring and cited lead profiles. Domain memory + evidence persisted to .research/ to survive compaction. Mieruka integration: drives the Research tab via MCP tools (list_research_threads, get_research_thread, update_research_thread) when .mieruka/ is present; falls back to file-mirror.

Structured Prompt-Driven Development workflow: story decomposition, analysis, REASONS Canvas, generation, prompt update, sync, API test, code review, and reverse engineering. Includes openspdd-ts CLI (bin/openspdd.mjs) for installing templates into any AI editor. Depends on pro-execution for disciplined implementation workflows. Adapted from gszhangwei/open-spdd.

Meta-plugin: installs Jody's default pro dev stack (core, pdd, execution, quality, design, motion, testing, data, nextjs, and research) plus worktrunk

The Verify phase: native Vitest (unit/component), agent-browser (interactive verification), and Storybook interactions, plus qa-suite — a bridge to the petrkindlmann/qa-skills library installed on demand via the /qa-engine command (npx skills add): qa-do/qa-start routers, playwright-automation, visual-testing, api/contract-testing, test-reliability, and QA strategy/risk/planning. Playwright is provided on demand via the qa-suite bridge (/qa-engine), not as a hard plugin dependency.

Premise validation — evidence-grade questioning, domain-aware probing, kill bad ideas early, earn the right to build

from probitas-test/claude-plugins

from probitas-test/claude-plugins

Guide teams through MITRE's Problem Framing Canvas for clearer problem statements.

Write a user-centered problem statement with who, what, why, and how it feels.

Plugin from arendon1/agent-skills

from gserafini/process-improvement

Lean Six Sigma process-improvement team — 2 specialist agents (lean-six-sigma-blackbelt, process-analyst) that analyze a team's operational processes and improve them with Black-Belt rigor: DMAIC, Lean waste removal (the 8 wastes / DOWNTIME), data-proven root-cause analysis, statistical process control, and control plans that make the gain stick. Domain-neutral (support, onboarding, billing, deployment, hiring — any process). 6 skills (dmaic-project-charter, process-mapping, root-cause-analysis, process-capability-and-spc, lean-waste-analysis, control-plan-and-sustain), 5 templates (charter, SIPOC, fishbone+5-Whys, FMEA, control-plan), 7 best-practices, and a 3-doc knowledge bank with 6 web-verified Mermaid decision trees (sigma/DPMO, Cp/Cpk, control-chart selection, Western-Electric/Nelson rules). The inferential statistics seam (hypothesis tests, DOE, regression, Gage R&R) routes to applied-statistics; DMAIC project delivery routes to project-management. Requires ravenclaude-core@>=0.7.0.

Process and task mining from M365, Power Automate, and Azure Monitor logs — extract event logs, discover process models, analyze performance, and check conformance

Identify and terminate processes by port number, process name, or PID. Cross-platform (Windows, macOS, Linux).

Procurement & Sourcing specialist team — 4 agents, 5 skills, 4-file cited knowledge bank, 3 templates, 5 commands, 8 best-practice rules, 1 advisory hook. A strategic-sourcing team for a procurement or category lead — it segments spend before it sources (the Kraljic should-cost lens), runs the sourcing event on total cost of ownership rather than unit price, manages supplier risk as a portfolio, and reads the spend cube the way a category manager who owns savings does. Inherits ravenclaude-core protocols.

Pre-production security audit, dependency hardening, CI/CD validation, and Docker readiness checks for Claude Code

Product-readiness audit past 'it compiles' — survives production, shippable (not a demo), makes money, and an award-winning UI. Council + Judge → ship / patch-then-ship / not-ready.

sumik Claude Code Plugin (product) — プロダクトマネジメント・要件定義スキル群（PRD/ロードマップ/ユーザーストーリー）

4 skills for product analytics, App Store marketing, monetization strategy, and onboarding

Product direction agent. Validation-driven, dialogue-based pipeline that designs product vision/mission/value, success metrics, revenue model, personas, customer journeys, positioning, UI mocks, features, data model, domains, API (system/process/experience), and SLA/NFR. Extracts and validates the riskiest assumptions before committing, and re-propagates changes via a traceability graph. Hands off to /architect for system implementation design.

Product Owner orchestrator + specialist agents and skills for INVEST review, backlog prioritization, and safe Azure DevOps work-item operations

Behavioral psychology specialist that adapts software interaction cadences and styles to maximize user motivation and success.

行为心理学、助推设计与用户激励专家

Turn a bootstrapped project into a working product by writing the PRD and building features.

Product-level planning and iteration: envision, map, model, dispatch, validate, calibrate, reflect, watch.

Product maps (PJM): capability view + journey playback with screenshots, product impact diffs, HTML deck export.

Shape product intent into shippable specs — and into the words users read. Habits — frame-intent, de-risk-intent, decompose-intent — over a recursive, level-tagged `intent` (product-vision, product-strategy, capability, and feature intents are the same artifact at different levels — Level is an open recognized set decoupled from Scale): outcome+opportunity framing, a choosable prototype-approach to de-risk the riskiest assumption, and decomposition into the briefs/specs your delivery loop already builds — at app scale, or sliced per component across a business-unit value stream coordinated by `align-value-stream`. `voice-and-microcopy` adds the content layer: characterize a product's voice and write blame-free, actionable UI copy. Pure-markdown, user-scope.

Requirements, user stories, MVP planning, prioritization, UX critique, and feedback-to-backlog