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 EngineerWithAI/engineerwith-agents --skill deployment-pipeline-designgit clone --depth 1 https://github.com/EngineerWithAI/engineerwith-agentsWrote 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/engineerwithai/engineerwith-agents/deployment-pipeline-design)<a href="https://agentmods.dev/skills/engineerwithai/engineerwith-agents/deployment-pipeline-design"><img src="https://agentmods.dev/badge/skills/engineerwithai/engineerwith-agents/deployment-pipeline-design.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.02071 |
| Opus 5 | $0.00020 | $0.01035 |
| Sonnet 5 | $0.00008 | $0.00414 |
| Haiku 4.5 | $0.00004 | $0.00207 |
Grade A, and why
deployment-pipeline-design scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
run: curl -f https://app.example.com/health This is a copy
91% identical to deployment-pipeline-design — 19 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 — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Pipeline Design
Architecture patterns for multi-stage CI/CD pipelines with approval gates and deployment strategies.
Purpose
Design robust, secure deployment pipelines that balance speed with safety through proper stage organization and approval workflows.
When to Use
- Design CI/CD architecture
- Implement deployment gates
- Configure multi-environment pipelines
- Establish deployment best practices
- Implement progressive delivery
Pipeline Stages
Standard Pipeline Flow
┌─────────┐ ┌──────┐ ┌─────────┐ ┌────────┐ ┌──────────┐
│ Build │ → │ Test │ → │ Staging │ → │ Approve│ → │Production│
└─────────┘ └──────┘ └─────────┘ └────────┘ └──────────┘
Detailed Stage Breakdown
- Source - Code checkout
- Build - Compile, package, containerize
- Test - Unit, integration, security scans
- Staging Deploy - Deploy to staging environment
- Integration Tests - E2E, smoke tests
- Approval Gate - Manual approval required
- Production Deploy - Canary, blue-green, rolling
- Verification - Health checks, monitoring
- Rollback - Automated rollback on failure
Approval Gate Patterns
Pattern 1: Manual Approval
# GitHub Actions
production-deploy:
needs: staging-deploy
environment:
name: production
url: https://app.example.com
runs-on: ubuntu-latest
steps:
- name: Deploy to production
run: |
# Deployment commands
Pattern 2: Time-Based Approval
# GitLab CI
deploy:production:
stage: deploy
script:
- deploy.sh production
environment:
name: production
when: delayed
start_in: 30 minutes
only:
- main
Pattern 3: Multi-Approver
# Azure Pipelines
stages:
- stage: Production
dependsOn: Staging
jobs:
- deployment: Deploy
environment:
name: production
resourceType: Kubernetes
strategy:
runOnce:
preDeploy:
steps:
- task: ManualValidation@0
inputs:
notifyUsers: '[email protected]'
instructions: 'Review staging metrics before approving'
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.
- 7d ago First seen · 360 lines · 41 tokens per session scan A 0c7343294b6f
deployment-pipeline-design is a skill published in the GitHub repository EngineerWithAI/engineerwith-agents (4 stars, last pushed 7mo ago), licensed MIT. It adds 41 tokens to every session and 2,071 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 91% identical to deployment-pipeline-design, differing in 19 lines, and is treated as a copy.
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