Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wewpellex21/code-sensei --skill deploymentgit clone --depth 1 https://github.com/wewpellex21/code-senseiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wewpellex21/code-sensei/deployment)<a href="https://agentmods.dev/skills/wewpellex21/code-sensei/deployment"><img src="https://agentmods.dev/badge/skills/wewpellex21/code-sensei/deployment/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wewpellex21/code-sensei/deployment"><img src="https://agentmods.dev/badge/skills/wewpellex21/code-sensei/deployment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.00608 |
| Opus 5.5 | $0.00015 | $0.00243 |
| Sonnet 5.5 | $0.00007 | $0.00122 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
deployment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to deployment — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment — CodeSensei Teaching Module
What is Deployment?
- Analogy: Deployment is moving from rehearsal to opening night. Your app works on your computer (localhost), and deployment puts it on a server so the whole world can use it.
- Key insight: When you run
npm starton your computer, only YOU can see the app. Deployment puts it on someone else's computer (a server) that's always on and connected to the internet.
Localhost vs Production
- localhost — your computer, only you can access it. The rehearsal stage.
- Production — a server in the cloud, anyone with the URL can access it. Opening night.
- Staging — a test server that mimics production. The dress rehearsal.
Common Deployment Platforms
- Vercel — one-click deployment for Next.js/React apps. Push to GitHub, it deploys automatically.
- Netlify — similar to Vercel, great for static sites and simple apps.
- Railway / Render — for backend apps with databases.
- AWS / GCP / Azure — the industrial-grade options. More complex but more powerful.
- Key insight: For most vibecoded projects, Vercel or Railway is all you need.
Domains & DNS
- Analogy: A domain name (like myapp.com) is a nickname for your server's actual address (an IP like 192.168.1.1). DNS is the phone book that translates names to addresses.
- Teaching flow: User types myapp.com → DNS looks up the address → Browser connects to the server → Server sends the app
Environment Variables in Production
- Key insight: Your .env file doesn't get uploaded. You set environment variables SEPARATELY in your hosting platform's dashboard.
- Why: Security. Your code is often public (on GitHub), but your secrets shouldn't be.
CI/CD (Continuous Integration / Continuous Deployment)
- Analogy: An automatic assembly line. Every time you push code to GitHub, the system automatically tests it, builds it, and deploys it — without you clicking anything.
- Key insight: This is why developers "push to main" to deploy. The pipeline handles the rest.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 42 lines · 37 tokens per session scan A ce325d1ced23
deployment is a skill published in the GitHub repository wewpellex21/code-sensei (3 stars, last pushed 3d ago), licensed MIT. It adds 37 tokens to every session and 608 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to deployment, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
infrastructure-planning
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relay-deploy
Set up a complete deployment configuration — Dockerfile, deployment manifest, environment config, and rollback procedure. Use when asked about "deployment setup", "how do I deploy this", "deployment strategy", or "rollback plan".
aws-cdk-development
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python. Use when creating CDK stacks, defining CDK constructs, implementing infrastructure as code, or when the user mentions CDK, CloudFormation, IaC, cdk synth, cdk deploy, or wants to define AWS infrastructure programmatically.…
deployment
Hosting, deployment, CI/CD, and going live. Activated when Claude works with deployment configs, Dockerfiles, Vercel/Netlify configs, or deployment-related commands.
aws-agentic-ai
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations. Covers agent deployment, MCP tool integration, credential…
aws-bedrock-ai
WORKFLOW SKILL — Amazon Bedrock and AWS AI design: foundation model selection, knowledge bases (RAG), agents for bedrock, guardrails, provisioned throughput, batch inference, fine-tuning, KMS, VPC endpoints, regional GA, and per-provider licensing.