Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/tahirraufkeeyu/software-development-agent-stack--sdas/deploy)<a href="https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/deploy"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/deploy.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 | $0.00048 | $0.02895 |
| Opus 5 | $0.00024 | $0.01448 |
| Sonnet 5 | $0.00010 | $0.00579 |
| Haiku 4.5 | $0.00005 | $0.00290 |
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 6d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use
- Promoting a release candidate to staging or production.
- Cutting over a blue/green stack after a schema migration.
- Running a canary at 5/25/50/100 percent with automated rollback.
- Any deploy that crosses an environment boundary guarded by approvals or SLOs.
Do not use for local kubectl apply against a dev cluster or for one-off hotfixes that bypass CI. For those, use kubectl rollout directly and document why.
Inputs
service— Kubernetes Deployment/StatefulSet name (e.g.checkout-api).namespace— target namespace (e.g.prod-us-east-1).image— fully qualified image reference (ghcr.io/acme/checkout-api:sha-abc1234).strategy—canary|blue-green|rolling.chart_path— path to the Helm chart used for this service.values_file— environment-specific values (e.g.values-prod.yaml).slo— an object:{ error_rate_max: 0.01, p95_latency_ms: 400, window_minutes: 5 }.canary_steps— list of percentages, e.g.[5, 25, 50, 100](canary only).approvers— GitHub environment approvers list for prod.
Outputs
- Rollout status summary (revision before/after, pods ready, traffic split).
- Prometheus/Datadog query results that the gate evaluated.
- Git SHA deployed, image digest, and Helm release revision.
- If rolled back: the triggering SLO metric, timestamp, and
helm rollbackoutput. - A Markdown deploy note suitable for posting to
#deploys.
Tool dependencies
kubectl>= 1.28, context already set to target cluster.helm>= 3.12.dockerorbuildxfor the image build step.cosignif the registry policy requires signed images.jq,yqfor parsing outputs.- Access to Prometheus (or Datadog/CloudWatch) for SLO queries.
- GitHub CLI (
gh) when the deploy is gated by a protected environment. - Optional: Argo Rollouts (
kubectl argo rollouts) if the project uses it.
Project scripts you supply
The procedure below shells out to two project-side scripts. They're not shipped by this skill — drop them in your repo at ./scripts/ (or adjust the paths). Section 7 below documents the exact query contract check-slo.sh must satisfy; smoke.sh is a thin wrapper around your service's existing health/smoke endpoint.
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.
- 6d ago First seen · 273 lines · 48 tokens per session scan A 4e4fb6854c4e
deploy is a skill published in the GitHub repository tahirraufkeeyu/software-development-agent-stack--sdas (18 stars, last pushed 4mo ago), licensed MIT. It adds 48 tokens to every session and 2,895 once invoked, about $0.0002 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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