By ilang-ai
Turn natural language app descriptions into live, deployed projects in one session: auto-generates plans with steps and estimates, scaffolds code, builds UIs, tests/runs/fixes bugs, applies security/performance best practices, deploys to Cloudflare/VPS/nginx, syncs via git across devices, and guides beginners on setup.
npx claudepluginhub ilang-ai/autocode --plugin autocodeClassify request as small/medium/large. Adjust workflow depth accordingly.
I-Lang compression engine. All internal planning uses I-Lang v3.0 syntax. Save 60%+ tokens. User never sees compressed output.
Record mistakes. Check before similar builds. Avoid repeating silently.
Detect recurring patterns in user's project. Apply automatically next time.
Learn user's preferences over time. Code style, naming, structure. Save to global prefs.
Persistent memory across sessions. Save project state and user preferences. Never save secrets.
Track project milestones. Auto-detect when a significant checkpoint is reached.
Help user work from multiple devices. Sync project via git.
Optimize for speed and cost. Pick lightweight solutions. Flag expensive operations.
Break complex tasks into 5-15 ordered steps with time estimates. Dependency order first.
Give realistic time and cost estimates for each step. Explain in human terms.
Decide what to build first. Core function before polish. Revenue before aesthetics.
Identify risks before building. Flag third-party dependencies, API limits, and cost traps.
Report progress after each feature. Percentage, what just completed, what comes next.
Create a visual roadmap for large projects. Phases, milestones, timeline.
Lock confirmed requirements. Don't change them without user approval.
Run and test directly on the server. No local dev environment needed. What you build is what goes live.
Save checkpoints before risky changes. Rollback if things break.
Build user-facing interface. Clean, functional, mobile-friendly by default.
Celebrate real milestones only. One line, one emoji. Credit belongs to user, not AI.
Create project skeleton. Pick stack, create files, install dependencies. AI decides everything.
Before coding, determine what to ask. Max 2 yes/no questions. Never ask technical questions.
Silent quality check after every feature. Fix issues before telling user. Never claim tests passed without running them.
When multiple solutions exist, pick the best one. Explain why in one sentence.
Build one feature at a time. Complete each fully before moving to next. Auto-triggers quality check.
Explain all costs in human terms. Always compare with real-world equivalents. Recommend cheapest that works.
End of session summary. What got done, what got fixed, what comes next, progress delta.
Translate technical decisions into human language. Explain in cost, speed, stability.
Deploy to Cloudflare Workers. Free tier handles 100k requests/day. Global edge network.
Choose deployment target based on project type. Static sites to CF Pages, APIs to VPS, serverless to Workers.
Deploy to VPS. Code is already on the server. Start the service, configure nginx, verify accessible.
Help user buy a domain, configure DNS, set up SSL. Guide every click.
At milestones, compare achievement vs human programmer time and cost. Keep it realistic.
Final go-live checklist. Is it accessible? SSL working? Mobile friendly? Show user their live URL.
Help complete beginners set up their development environment. Detect Mac or other. Guide VPS purchase and SSH setup step by step.
Transfer files between local and server. Guide user through SCP or upload methods.
Auto-fix bugs. Observe symptom, find root cause, apply minimal fix, verify, explain in human terms.
After fixing a bug, explain what went wrong in language the user understands. No jargon for beginners.
Guide user through errors they see. Translate error messages to human language.
Step 1 of debugging: observe the symptom carefully before jumping to conclusions.
Step 2 of debugging: reason about root cause based on observed symptoms.
Step 3 of debugging: apply minimal fix. One-liner ideal. Verify nothing else broke.
Full project review from beginning. Check every file. Plain language report.
Auto-apply security basics. Never ask user about security choices. Just do it.
::GENE{autocode|conf:confirmed|scope:global}
Detect user's intent from their message and activate the right workflow silently.
Detect user's technical level from first messages. Adjust all output language accordingly.
Claude Code skill pack for Replit (30 skills)
Share bugs, ideas, or general feedback.
Enhances Claude Code from producing raw code into delivering production-ready systems. 14 specialized agents handle architecture, tested code, security audit, CI/CD, and documentation. Use for building apps/websites/services, adding features, hardening, deployment, testing, review, or architecture design.
Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare. Originally from OpenAI's curated skills catalog.
Full-stack web development with app scaffolding and page generation
Use this agent when setting up CI/CD pipelines, configuring Docker containers, deploying applications to cloud platforms, setting up Kubernetes clusters, implementing infrastructure as code, or automating deployment workflows. Examples: <example>Context: User is setting up a new project and needs deployment automation. user: "I've built a FastAPI application and need to deploy it to production with proper CI/CD" assistant: "I'll use the deployment-engineer agent to set up a complete deployment pipeline with Docker, GitHub Actions, and production-ready configurations."</example> <example>Context: User mentions containerization or deployment issues. user: "Our deployment process is manual and error-prone. We need to automate it." assistant: "Let me use the deployment-engineer agent to design an automated CI/CD pipeline that eliminates manual steps and ensures reliable deployments."</example>
Specialist AI engineering team for Claude Code. 8 agents with HITL checkpoints, handoff contracts, structured memory, and /agency-run orchestrator.