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 agentmods add skills/fattain-naime/engineering-docs/deployment-plannpx skills add fattain-naime/engineering-docs --skill deployment-plangit clone --depth 1 https://github.com/fattain-naime/engineering-docsWhat 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 | $0.00054 | $0.03716 |
| Opus 5 | $0.00027 | $0.01858 |
| Sonnet 5 | $0.00011 | $0.00743 |
| Haiku 4.5 | $0.00005 | $0.00372 |
Grade A, and why
deployment-plan 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.
How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Produce a deployment plan that specifies exactly how, when, and by whom a release is deployed, what criteria determine success or failure, and what steps to take if something goes wrong.
A deployment without a rollback plan is a deployment without a safety net. This skill ensures every production change is made with eyes open and a clear path back.
Input
Works best with: The name of the service being deployed and a description of what is changing. Also valuable: Current production environment specs, existing deployment pipeline, known risks or dependencies, SLA requirements.
Example invocation: Write a deployment plan for releasing PayFlow v2.4.0 to production. This release includes 3 database migrations (additive only), a new webhook delivery queue worker, and updates to the checkout templates. We use a single production server with PHP-FPM and MySQL. Zero downtime is required.
Key Concepts
Deployment Strategies
- Direct Deploy: Replace running code in-place. Simple, but brief downtime risk.
- Rolling Deploy: Update instances one at a time. No downtime. If failure occurs, some instances run old code while others run new.
- Blue-Green: Maintain two identical environments (Blue = current, Green = new). Switch traffic at load balancer after validation. Zero downtime. Full instant rollback by switching back.
- Canary: Deploy to small percentage of traffic first (e.g., 5%). Monitor. Gradually increase if metrics hold.
- Feature Flag: Deploy code to all servers but enable via config. Decouple deployment from release.
Strategy Decision Matrix
Choose the deployment strategy based on three factors: risk tolerance, downtime tolerance, and infrastructure capability.
| Risk Level | Downtime OK? | Infrastructure | Recommended Strategy |
|---|---|---|---|
| Low | Yes | Single server | Direct Deploy |
| Low | No | Multiple instances | Rolling Deploy |
| Medium | No | Load balancer available | Blue-Green |
| High | No | Load balancer + metrics pipeline | Canary |
| Any | No | Feature flag system in place | Feature Flag |
| High | No | Kubernetes / ECS | Canary with pod-level rollback |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 249 lines · 54 tokens per session scan A 0ec4d0c817c3
deployment-plan is a skill published in the GitHub repository fattain-naime/engineering-docs (4 stars, last pushed 18d ago), licensed MIT. It adds 54 tokens to every session and 3,716 once invoked, about $0.0003 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 2026-08-31.
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