Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sjarmak/coding-agent-workflowsnpx agentmods add skills/sjarmak/coding-agent-workflows/deployment-patternsWrote 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/sjarmak/coding-agent-workflows/deployment-patterns)<a href="https://agentmods.dev/skills/sjarmak/coding-agent-workflows/deployment-patterns"><img src="https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/deployment-patterns/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/sjarmak/coding-agent-workflows/deployment-patterns"><img src="https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/deployment-patterns.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 | $0.00031 | $0.02904 |
| Opus 5.5 | $0.00012 | $0.01162 |
| Sonnet 5.5 | $0.00006 | $0.00581 |
| Haiku 4.5 | $0.00003 | $0.00290 |
Grade A, and why
deployment-patterns 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1 This is a copy
88% identical to deployment-patterns — 22 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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deployment Patterns
Use the project's installed version and conventions. Verify version-sensitive APIs,
security settings, and deployment support with documentation-lookup before
applying examples; these patterns are reference guidance, not a tested guarantee
for every current release. Do not replace an existing toolchain solely to match
an example.
Production deployment workflows and CI/CD best practices.
When to Activate
- Setting up CI/CD pipelines
- Dockerizing an application
- Planning deployment strategy (blue-green, canary, rolling)
- Implementing health checks and readiness probes
- Preparing for a production release
- Configuring environment-specific settings
Deployment Strategies
Rolling Deployment (Default)
Replace instances gradually — old and new versions run simultaneously during rollout.
Instance 1: v1 → v2 (update first)
Instance 2: v1 (still running v1)
Instance 3: v1 (still running v1)
Instance 1: v2
Instance 2: v1 → v2 (update second)
Instance 3: v1
Instance 1: v2
Instance 2: v2
Instance 3: v1 → v2 (update last)
Pros: Zero downtime, gradual rollout Cons: Two versions run simultaneously — requires backward-compatible changes Use when: Standard deployments, backward-compatible changes
Blue-Green Deployment
Run two identical environments. Switch traffic atomically.
Blue (v1) ← traffic
Green (v2) idle, running new version
# After verification:
Blue (v1) idle (becomes standby)
Green (v2) ← traffic
Pros: Instant rollback (switch back to blue), clean cutover Cons: Requires 2x infrastructure during deployment Use when: Critical services, zero-tolerance for issues
Canary Deployment
Route a small percentage of traffic to the new version first.
v1: 95% of traffic
v2: 5% of traffic (canary)
# If metrics look good:
v1: 50% of traffic
v2: 50% of traffic
# Final:
v2: 100% of traffic
Pros: Catches issues with real traffic before full rollout Cons: Requires traffic splitting infrastructure, monitoring Use when: High-traffic services, risky changes, feature flags
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 · 433 lines · 31 tokens per session scan A bb305c5b6bd2
deployment-patterns is a skill published in the GitHub repository sjarmak/coding-agent-workflows (7 stars, last pushed 10d ago), licensed MIT. It adds 31 tokens to every session and 2,904 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 88% identical to deployment-patterns, differing in 22 lines, and is treated as a copy.
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