A deployment tool that builds a Docker image for a specific coding-agent team from its team manifest. A Docker image is a packaged environment used to run software.

Use it to validate a team manifest, generate team instructions, and build the team’s Docker image.

It checks the team definition and required base images before producing a restricted, team-specific worker environment.

deploy-team — Skill for Claude Code by SteveGJones

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code

/plugin marketplace add SteveGJones/ai-first-sdlc-practices

Claude Code

/plugin install sdlc-workflows

Made for: Claude Code.

Or install sdlc-workflows, the plugin that ships this one along with the rest of its 6 skills, 1 agent.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/deploy-team/github.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/deploy-team)

Your own site

<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/deploy-team"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/deploy-team/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/deploy-team"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/deploy-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 641 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00044	$0.00641
Opus 5.5	$0.00018	$0.00256
Sonnet 5.5	$0.00009	$0.00128
Haiku 4.5	$0.00004	$0.00064

Measured 1mo ago against content hash cfe3a78e3ec3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deploy-team 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 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.

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.

plugins/sdlc-workflows/skills/deploy-team/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deploy Team Image

Build a team-specific Docker image from a team manifest.

Arguments

--name <team-name> (required) — team manifest in .archon/teams/<team-name>.yaml
--image <tag> (optional) — custom image tag (default: sdlc-worker:<team-name>)

Steps

1. Read and validate the manifest

Read .archon/teams/<team-name>.yaml. Validate:

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/validate_team_manifest.py \
    .archon/teams/<team-name>.yaml \
    --installed-plugins "${CLAUDE_PLUGINS_DIR:-$HOME/.claude/plugins}/installed_plugins.json" \
    --project-root .

If validation fails, report errors and stop. Check status field — refuse to build inactive or decommissioned teams.

2. Verify base and full images exist

docker image inspect sdlc-worker:base >/dev/null 2>&1
docker image inspect sdlc-worker:full >/dev/null 2>&1

If missing, inform user and offer to build them:

bash ${CLAUDE_PLUGIN_ROOT}/docker/build-base.sh
bash ${CLAUDE_PLUGIN_ROOT}/docker/build-full.sh

3. Generate team CLAUDE.md

Use the generate_team_claude_md.py script to create the team's CLAUDE.md from the manifest:

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/generate_team_claude_md.py \
    .archon/teams/<team-name>.yaml \
    --installed-plugins "${CLAUDE_PLUGINS_DIR:-$HOME/.claude/plugins}/installed_plugins.json" \
    --output .archon/teams/.generated/<team-name>-CLAUDE.md

If the project has a CLAUDE.md, concatenate it (project first, team second).

4. Build the team image

bash ${CLAUDE_PLUGIN_ROOT}/docker/build-team.sh <team-name> [--image <tag>]

This generates a Dockerfile with additive copy-only (no prune) and builds the image. The generated Dockerfile and CLAUDE.md go to .archon/teams/.generated/.

5. Update manifest timestamp

After successful build, update image_built in the manifest YAML to current ISO-8601 datetime.

6. Report

Report the following:

Image name and tag
Image size (from docker image inspect)
Agent count and skill count (from manifest)
Generated file locations (Dockerfile and CLAUDE.md)

Read the full file on GitHub · 74 lines

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.

1mo ago First seen · 74 lines · 44 tokens per session scan A cfe3a78e3ec3

Subscribe to this mod's changes

deploy-team is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 44 tokens to every session and 641 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.

Building agents Containers DevOps and cloud

deploy-docker-compose

Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…

omnigent-ai/omnigent · 84 tokens

bdd-container-update

Update the BDD test container image when its dependencies or runtime change. Determines version bump (major vs minor vs patch), rebuilds the Docker image, pushes to GitLab registry, and updates the image tag in starttest.sh. Test source (tests/, features/, scripts/, data/, conftest.py) is bind-mounted from the host…

NVIDIA-AI-Blueprints/video-search-and-summarization · 117 tokens

securing-kubernetes-on-cloud

This skill covers hardening managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring. It addresses cloud-specific security features including IRSA for EKS, Workload Identity for…

xalgorix/xalgorix · 80 tokens

deploy-team