deploy

A deployment procedure for moving an application to a staging or production environment, where staging is a testing copy and production is the live system.

In plain words
What is it for?
Use it to build a Docker image, upload it to a container registry, update an AWS ECS service, test the health endpoint, and report the result.
Why use it?
It reduces the risk of releasing broken code by requiring tests, lint checks, a build, a health check, and a rollback if the live check fails.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/bdfinst/agentic-dev-team/deploy
Any agent
npx skills add bdfinst/agentic-dev-team --skill deploy
Clone the repo
git clone --depth 1 https://github.com/bdfinst/agentic-dev-team

Made for: Claude Code, Codex.

Per session 10 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 256 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00010 $0.00256
Opus 5 $0.00005 $0.00128
Sonnet 5 $0.00002 $0.00051
Haiku 4.5 $0.00001 $0.00026

Measured 2d ago against content hash aa75ea1bab3d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deploy 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 2d 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.

evals/fixtures/cs-complete-setup/.claude/skills/deploy/SKILL.md · 46 lines

What it actually says

Deploy

Parse Arguments

Arguments: $ARGUMENTS

  • staging (default): deploy to staging environment
  • production: deploy to production (requires staging green)

Steps

1. Run pre-deploy checks

Run npm test and npm run lint. Abort if either fails.

2. Build artifacts

Run npm run build. Verify the dist/ directory is created.

3. Build Docker image

Run docker build -t app:$(git rev-parse --short HEAD) .

4. Push to registry

Run docker push $ECR_REPO:$(git rev-parse --short HEAD)

5. Update service

Run aws ecs update-service --cluster $CLUSTER --service $SERVICE --force-new-deployment

6. Smoke test

Hit the /health endpoint. If it returns non-200 after 60 seconds, trigger rollback.

7. Report

Print deployment status: image tag, environment, timestamp, health check result.

Changes

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.

  1. 2d ago First seen · 46 lines · 10 tokens per session scan A aa75ea1bab3d

Subscribe to this mod's changes

deploy is a skill published in the GitHub repository bdfinst/agentic-dev-team (277 stars, last pushed yesterday), licensed MIT. It adds 10 tokens to every session and 256 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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