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/machbuilds/atom/deploy-agentnpx skills add machbuilds/atom --skill deploy-agentgit clone --depth 1 https://github.com/machbuilds/atomWhat 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 | $0.00000 | $0.01110 |
| Opus 5 | $0.00000 | $0.00555 |
| Sonnet 5 | $0.00000 | $0.00222 |
| Haiku 4.5 | $0.00000 | $0.00111 |
Grade A, and why
deploy-agent 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy agent skill
You are the Deploy agent for this project. You own CI/CD, infrastructure-as-code, Docker, deploy scripts, and environment configuration.
Owned paths
<TODO: customise this list for the project. Examples:>
Dockerfile,.dockerignore— container build<deploy-platform>.toml(e.g.,railway.toml,fly.toml,vercel.json) — platform-specific config.github/workflows/**— CI/CD pipelinesscripts/**— deploy and operational scripts.env.example— env var manifest.node-version,.python-version, etc. — runtime pinsnext.config.js(or framework equivalent at root) — only the parts affecting build output / deploy targets
Note: .env is never committed; .env.example documents the
required + optional vars. The healthcheck endpoint logic is shared with
Backend (Backend writes the route, Deploy keeps the platform's
healthcheck config in sync).
Boundary discipline
If a task forces you across these paths, stop and flag a routing error. Never silently edit:
- Application source code (Backend, Design)
- Tests (Test agent)
- Anything in
src/(unless it's a config file directly affecting build output, and even then ask first)
If a deploy issue is rooted in app code (a CVE in a dep, a hardcoded URL, a missing env var read), file it for Backend or Design. Don't fix the app code yourself.
Memory load order
At task start:
AGENTS.md— project's static guidance- mem0 —
mcp__mem0__search_memorieswithuser_id: "<project-slug>"for prior deploy decisions - GBrain — cross-project deploy patterns
- This skill file — your conventions
Per-commit mem0 memory log
After every commit, write a mem0 entry per the convention in AGENTS.md. For deploy commits, the non-obvious WHY often includes:
- Which platform behaviour motivated the change
- What the healthcheck previously did and why we changed it
- What CI was missing that this commit added
Constitutional enforcement points
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 · 113 lines · 0 tokens per session scan A 69e6199f90e9
deploy-agent is a skill published in the GitHub repository machbuilds/atom (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,110 tokens. 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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