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By JaviMontano
JM Agentic Development Kit — 611 skills (incl. the 30 Claude Certified Architect katas and the Jarvis OS capability pack), 261 agents, 267 commands, safe first-use onboarding, skill scaffolding, local-first workspaces, validation gates, and upgrade-safe GitHub sync.
npx claudepluginhub javimontano/jm-adk-alfaExtract requirements from conversation/documents
Generate prioritized product roadmap
Blue-green, canary, feature flags, database rollback patterns.
Rollback to previous deployment
One-pagers, battle cards, ROI calculators, competitive positioning documents.
WCAG implementation, screen reader testing, ARIA patterns
Hypothesis formulation, statistical significance, sample size calculation, test duration.
WCAG 2.1 auditing, axe-core, screen reader testing
Designs WCAG 2.1 AA compliant patterns including ARIA roles, keyboard navigation, and screen reader support.
Alt text guidelines, plain language, reading level, inclusive language.
Designs and reviews A/B tests with explicit hypothesis, primary metric, guardrail metrics, variants, sample-size assumptions, duration, stopping rules, instrumentation checks, and decision criteria. [EXPLICIT] Trigger: "ab testing, a/b test, experiment design, split test, hypothesis formulation, statistical significance, sample size calculation, test duration"
WCAG 2.1 AA automated scanning with axe-core plus manual checklist for keyboard, screen reader, and contrast
Designs and implements WCAG 2.1 AA accessibility patterns for web applications using native HTML first, targeted ARIA only when needed, keyboard interaction maps, focus management, screen reader semantics, contrast tokens, accessible forms, reduced motion, and inclusive interaction requirements. [EXPLICIT] Trigger: "accessibility", "WCAG", "ARIA", "a11y", "screen reader", "inclusive design"
Plan, execute, and report web accessibility tests with axe-core, Playwright/Jest evidence, keyboard scripts, screen reader smoke checks, color contrast validation, and explicit WCAG target scope. [EXPLICIT] Trigger: "accessibility test", "a11y test", "WCAG test", "screen reader", "axe-core", "keyboard accessibility"
Rewrite and review content so it is accessible, understandable, inclusive, and safe to publish: alt text, plain language, reading-level estimates, descriptive links, helpful errors, non-sensory instructions, localization, and evidence-backed limits. [EXPLICIT] Trigger: "accessibility writing", "accessible copy", "alt text", "plain language", "inclusive language", "reading level", "descriptive links"
Requires secrets
Needs API keys or credentials to function
Uses power tools
Uses Bash, Write, or Edit tools
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Give soul to your workflow. 58 AI-powered skills across 17 roles — PM, Dev, Backend, Frontend, QA, UX, Data, Detect, WordPress, Release, Security, DevOps, and Core. Spec-to-ship pipeline: scaffold, implement, test, secure, deploy. Features two-phase workflow with human approval, quality-reviewer agent, token optimization, and continuous improvement via LEARN.md system.
50 specialist skills + 43 slash commands for coding agents — orchestrator, backend, frontend, QA, security, deploy, detective-spec, static-analysis, skill-author, program-router, parallel-dispatcher, blog-publisher, blog-screenshot, canary-deployment, zoom-out, handoff-context, post-deploy-canary-monitor, pattern-conformity, research-prep, context-budget, direct-response-copy, ux-research + spec-driven development, anti-AI writing, memory consolidation, executable YAML pipelines + insights dashboard (v2.18.0, 6 tabs). v2.37.0: absorcao de 7 ebooks Casa do Codigo — skill 50 ux-research (gap real: discovery qualitativo — entrevista, persona baseada em pesquisa, journey map, teste de usabilidade, arquitetura de informacao; antecede PO 01 e UI/UX 02) + 3 policies de XP (pair-programming, continuous-integration, sustainable-pace, ligadas a skill 37) + incrementos cirurgicos: skill 01 ganha Fundamento de Negocio (validacao de hipotese, MVP, monetizacao, AARRR, product-market fit — do Guia da Startup); skill 14 ganha Keyword Research (KEI, intent, cauda longa) + Off-Page/Link Building (do SEO Pratico); skill 07 ganha Infrastructure as Code (provisionamento declarativo, idempotencia, drift — principios do DevOps na pratica traduzidos pra Terraform/Ansible); skill 38 ganha lentes de coesao/acoplamento, seam distribuido (REST/async/RPC, HATEOAS) e camadas (da Introducao a Arquitetura). Livros de Jogos HTML5 Canvas (nicho <2%) descartados por frequencia. v2.36.0: skill 50 direct-response-copy — copy de direct response destilada de 3 ebooks classicos PT-BR: biblioteca de formulas de headline em 20 categorias de gatilho (357 modelos destilados em formulas parametrizadas), 8 gatilhos mentais + storytelling de venda, copy de Instagram (legenda/engajamento). Gate de integridade obrigatorio: sem claim nao-verificavel, sem depoimento fabricado, escassez so real. Complementa a skill 13 (copy de produto): 13 cobre landing/microcopy/brand voice, 50 cobre ads/pagina de vendas/email/social. v2.35.0: auto-skillify (absorcao parcial do activeloopai/hivemind) — hook UserPromptSubmit que a cada N turnos (default 20) injeta checkpoint perguntando se a atividade recente vale virar learned-skill (3 criterios: nao-googleavel, especifico do codebase, custou debugging). Adapta o skillify-via-Haiku do hivemind ao runtime: delega a decisao ao agente da sessao (ja pago) em vez de forkar LLM. Le a contagem do context-turn-counter. O resto do hivemind ja tinhamos: codebase graph=Graphify, semantic search=.index/vault.db, memory compound=memory-curator. v2.34.0: vault de memoria UNIFICADO ao kit — instalar o kit agora CRIA o vault automaticamente (scripts/init-vault.mjs roda no install.sh: cria estrutura logs/architecture/secrets, CLAUDE.md com as regras de escrita, .gitignore protegendo secrets/, git init). Path PORTAVEL via scripts/vault-resolver.mjs: $CLAUDE_MEMORY_VAULT → ~/.claude-memory (novo padrao, vale Windows/Mac/Linux) → D:/claude-memory (legado). Antes o vault era montado a mao e o path hardcoded; agora kit+memoria sao uma coisa so. Idempotente (nao sobrescreve vault existente). v2.33.0: absorcao obsidian-second-brain (memoria AI-first) — policy memory-write-rules.md aplica anti-fabricacao ao VAULT (false-absence: busque exaustivamente antes de afirmar que nao existe nota/decisao — o failure mode mais comum; no-fabrication: TBD para desconhecido; recency markers '(as of YYYY-MM, fonte)' em claims externos; niveis de confianca) + convencao 'For future Claude' (preambulo de 2-3 linhas que o futuro-Claude le em 10s pra decidir relevancia, no skill 31 session-summary) + comando /reconcile-memory (detecta contradicoes no vault — decisoes revertidas/superadas nunca atualizadas — e resolve: mais novo+autoritativo vence com secao ## History, ambiguo vira flag, evolucao marca superseded). v2.32.0: pre-build-gate (UserPromptSubmit hook) leva o 'pare e decida antes de codar' de cada disciplina (que o /auto tem nas fases) para o MODO PASSIVO — detecta intencao de criacao no prompt e injeta o checklist da disciplina certa: acceptance-criteria (defina done antes de implementar), api-contract (formato de erro + status codes antes da 1a rota), schema-integrity (constraints/FK/indices antes do 1o INSERT), ui-design (ancora estetica antes de estilizar), deploy-readiness (healthcheck/env/graceful-shutdown). 4 novas rules path-scoped por disciplina (rules/backend/, rules/database/, rules/frontend/, rules/common/acceptance-criteria.md). v2.31.0: design-aware /auto — fase UI-DESIGN como gate (PLAN→[UI-DESIGN]→BUILD) que invoca skill 02-ui-ux-design e bloqueia build de arquivo visual ate a ancora estetica estar escolhida; rules/frontend/ui-design.md (path-scoped em .css/.tsx/public) proibe o default generico (#4f46e5 indigo + system-ui), forca escolher 1 ancora; coverage config virou gate HARD no /auto; scope inference (app→fullstack) movido pra rules/common para o modo passivo herdar. Validado por bench A/B real (bench/ab/, 3 rounds) que expos UI generica nos 3 bracos. v2.29.0: claim-verifier (PostToolUse — detecta afirmacoes sem evidencia: 'email enviado', 'deploy OK', 'teste passou'; passa livre se ha exit code 0/HTTP 200/query result) + context-turn-counter (UserPromptSubmit — compact a cada 25 turnos, handoff inteligente a cada 50 usando vault de memoria). v2.28.0: /spec-kit (SDD pipeline unificado specify→plan→tasks→implement + Adversarial Verifier inline), /insights (recomendacoes baseadas em telemetria dos hooks), /swarm com Phase 3 Adversarial Verify (Implementor vs Verifier com goals opostos, spec atualizada em real-time). v2.27.0: investigate-first guard (hook PreToolUse que impede a IA de perguntar o auto-descobrivel — gh user, branch, package manager, porta, versao de runtime — manda investigar primeiro) + policy investigate-first. v2.26.0: silent-failure-hunter (16o subagent, review-only: caca catch{} vazio, swallowed errors, fallbacks perigosos, stack traces perdidos, rollback faltando) + skill 49 context-budget (audita peso de contexto carregado por componente) + /context-budget. v2.25.0: rules system path-scoped (`.claude/rules/` com `paths:` glob, inspirado no ECC), bug-fix da allowlist de subagents, 5 skills stub reescritos com profundidade. v2.24.0: curador AUTONOMO de memoria (inspirado no Hermes Agent) — roda async no SessionStart, faz decay/archive/dedup em JS puro sem gastar LLM e delega so a parte semantica ao agente presente. v2.23.0: absorcao addozhang (skill 48 research-prep, Spring Boot playbook, mem9 patterns). v2.22.0: memory curator nudge. v2.21.0: context-cost guards. v2.20.0: skill 47 pattern-conformity. 16 dispatchable subagents.
Autonomous multi-agent development framework with spec-driven sprints and convergent iteration
🚀 Quick Flow Solo Dev — Elite Full-Stack Developer + Quick Flow Specialist
Four-layer test framework for Claude Code plugin skills — structure validation, trigger accuracy, session testing, and skill value comparison
Lean agent skills for building, shipping, strategy, and growth — no context bloat.
Sovereign Architect — Evidence-based technical leadership for software engineering. 66 specialists · 127 skills MOAT · 119 commands · 19 scripts · 13 ontology files · 39 RAG docs · 4 quality gates (G0-G2). Development Kit Edition: Supabase, Firebase, React, Angular, Vue, Next.js, PostgreSQL, MongoDB, Redis, CSS architecture, web performance, scaffolding. Zero-assumption protocol.
Plugin QA — Full plugin development lifecycle for Claude Code plugins. 4 agents, 20 skills, 31 commands, 9 scripts, 13 ontology files, 9 movements (IDEATE, PLAN, DESIGN, SPECIFY, BUILD, VALIDATE, AUDIT, REPORT, FIX). Session automation with hooks, living ontology, and the autoridad moral: the plugin that audits plugins passes its own standards.
PQA — Plugin Quality Auditor. Plugin development lifecycle management: ideate, plan, design, specify, build, validate, audit, report, and fix plugins. 4 agents, 20 skills, 31 commands.
SDD — Spec Driven Development by MetodologIA. Specification-driven AI development with cryptographic BDD verification, autonomous heartbeat sentinel, insights engine, and Neo-Swiss lifecycle dashboard. Powered by IIC/kit.
PMO-APEX v1.0 — Agentic Project Excellence. Living ontology (CLAUDE.md hub + 13 sub-files), progressive MOAT loading (L1/L2/L3), G0 security gate, context optimization, rendering engine, CLI init wizard, PM retrospective, browser audit (MCP Playwright), cross-platform skill conversion, meta-cognition protocols (FULL/LIGHT), formalized committee spawning (Steering Committee 7 Advisors). 48 agentes, 109 skills MOAT, 103 comandos, 19 scripts, 5 quality gates (G0-G3). Zero-hallucination protocol. Evidence tagging obligatorio. NUNCA precios — solo magnitudes de esfuerzo.
Version: 5.2.0 License: MIT Repository: https://github.com/JaviMontano/jm-adk-alfa
JM-ADK is a local-first agentic development kit for AI-assisted software work. It packages skills, agents, commands, prompts, workspace governance, guardrails, and validation scripts so a developer can scaffold, run, review, and update agentic workflows without mixing versioned kit files with local state.
The authoritative counts come from python3 scripts/count-components.py.
| Component | Count |
|---|---|
| Skills | 601 |
| Agents | 261 |
| Commands | 267 |
| Prompts | 256 |
| Total physical components | 1368 |
JM-ADK ships the 30 Claude Certified Architect katas as first-class, executable katas-* skills (one per kata) across the 5 exam domains:
| Domain | Weight | Katas |
|---|---|---|
| D1 · Agentic Architecture | 27% | deterministic-agent-loop, pretooluse-guardrails, posttooluse-normalization, hub-and-spoke-isolation, headless-code-review, human-handoff-protocol, adaptive-investigation, multiagent-error-propagation |
| D2 · Tool Design & MCP | 18% | defensive-structured-extraction, mcp-structured-errors, tool-description-quality, mcp-server-configuration, builtin-tool-selection |
| D3 · Claude Code Config | 20% | plan-mode-exploration, hierarchical-claude-memory, path-conditional-rules, custom-commands-skills, session-resume-fork |
| D4 · Prompt & Structured Output | 20% | fewshot-edge-calibration, critical-self-correction, message-batch-processing, validation-retry-feedback, independent-reviewer-multipass, confidence-stratified-sampling, false-positive-criteria |
| D5 · Context & Reliability | 15% | prefix-caching, context-dilution-mitigation, multipass-prompt-chaining, persistent-scratchpad, provenance-preservation |
The katas are backed by systemic reliability infrastructure: a policy-driven PreToolUse guard (references/guardrails/tool-policy.json), reliability references (references/reliability/), a structured-annotation schema + headless CI workflow (.github/workflows/validate.yml), a Message Batches runner (scripts/batch/), and QA suites (scripts/qa/). Source inventories live in docs/katas/.
git clone https://github.com/JaviMontano/jm-adk-alfa.git
cd jm-adk-alfa
python3 scripts/count-components.py
python3 scripts/validate-skills.py --strict
Before the first task, diagnose local readiness:
python3 scripts/diagnose-first-use.py --dry-run
If the first user input is only hola, buenas, hey, hello, or empecemos, Alfa should start /jm-adk:first-use instead of beginning technical work. The guided setup asks for goal, project type, stack, preferred runtime, autonomy level, command policy, privacy constraints, workspace area, and output format.
Create local profile state only after review:
python3 scripts/setup-workspace-profile.py --dry-run
python3 scripts/setup-workspace-profile.py --apply
Declare which runtimes you will drive the kit from (validated against the known
set: claude-code, claude-desktop, claude-cowork, codex, gemini-cli,
antigravity, cursor, windsurf, vscode-copilot):
python3 scripts/setup-workspace-profile.py \
--runtime claude-code \
--runtime-targets claude-code,claude-desktop,codex,antigravity \
--apply
The profile lives in .jm-adk.local.json (schema 2, with preferredRuntime +
runtimeTargets) and must remain untracked.
The kit ships one MCP server, workspace-mcp (Gmail + Google Workspace, OAuth2).
It runs on every supported runtime; the config file and snippet differ per runtime.
python3 scripts/generate-mcp-configs.py --apply # write references/mcp/*.example
python3 scripts/validate-mcp-config.py # check wiring is coherent + secret-free
Per-tool × per-runtime wiring (Claude Code, Claude Desktop, Codex, Gemini CLI,
Antigravity, Cursor, Windsurf, VS Code): docs/runtime-tool-access-matrix.md.
OAuth setup: docs/google-workspace-mcp-setup.md.
Alfa includes an in-kit context repo at user-context/. It is identified by
user-context/.jm-adk-context.json, so it remains recognizable as the user
context area regardless of what files the user later adds there.
Use it for durable user background, preferences, memory, curated resources/,
and personal-skills/ that should survive across workspaces. It is separate
from workspace/, which is task runtime state.
python3 scripts/diagnose-user-context.py --dry-run
python3 scripts/diagnose-personal-skills.py --dry-run
python3 scripts/scaffold-user-context.py --dry-run
Personal context content is ignored by git by default. Only the scaffold, marker, schemas, and docs are tracked.
Versioned kit files live in the repo. Local runtime state does not.
Tracked: