deploy

A deployment-monitoring command for GitHub Actions, the service that runs automated build and release jobs. It watches a deployment, investigates failures, reruns it when requested, and checks that the app is healthy.

In plain words
What is it for?
Use it to inspect deployment runs, identify failing jobs, classify likely causes, rerun a deployment, and verify the resulting application and infrastructure health.
Why use it?
It reduces the time spent finding the failed job and reading its logs when a release does not complete. It also keeps deployment changes controlled by requiring confirmation before starting or rerunning one.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/robofinsystems/robosystems/deploy
Clone the repo
git clone --depth 1 https://github.com/RoboFinSystems/robosystems

Made for: Claude Code.

Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,347 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00018 $0.01347
Opus 5 $0.00009 $0.00674
Sonnet 5 $0.00004 $0.00269
Haiku 4.5 $0.00002 $0.00135

Measured 2d ago against content hash 366a141d527d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deploy 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 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -sf https://<api-host>/v1/status && echo OK # public API over HTTPS
.claude/commands/deploy.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Monitor a deployment run — pinpoint why it failed, drive it to green on a re-run, and verify health. Deploys go through GitHub Actions (workflow_dispatch); this skill is about watching and diagnosing them, not replacing the pipeline. Pairs with the deployment-monitoring runbook in local/RoboSystems/runbooks/ for account-specific stack names and failure classes — read it alongside this file.

When this runs

Most deploys (~95%) go green untouched and need no attention. The real use case is the other 5%: a deploy failed, and you're re-running it and want eyes on this one. Optimize for that — get to the failing job fast, classify it, fix the cause, re-trigger, and confirm the app is healthy afterward.

Scope & guardrails

  • gh reads are free; the deploy trigger is not. Reading runs, jobs, and logs (gh run list/view/watch) needs no confirmation. Triggering or re-triggering a deploy (gh workflow run, just deploy) is an outward-facing action — confirm the target (env + ref) with the user first, and default to watching a run they already started.
  • AWS is read-only here. describe-* / list-* only. CloudFormation changes and stack deletions are the user's to run — never create-stack/update-stack/delete-stack directly.
  • Never deploy the default branch to prod. Production should ride a version tag / release branch produced by the release workflow. Verify the ref before triggering rather than assuming the pipeline will reject a bad one, and when reviewing history (gh run list --json headBranch,displayTitle), flag any past prod run that rode a branch rather than a tag.
  • just deploy defaults are dangerous if you're not explicit. The recipe defaults to the prod environment and the current branch. Always pass both arguments.
  • Output can be sensitive. Failure logs name internal hostnames, stack names, and resource IDs. Don't paste raw infra detail into anything public; summarize.

1. Find the run

Identify env (staging | prod) and which run you're looking at. If the user didn't say, ask or infer from context.

Read the full file on GitHub · 73 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.

  1. 2d ago First seen · 73 lines · 18 tokens per session scan A 366a141d527d

Subscribe to this mod's changes

deploy is a command published in the GitHub repository RoboFinSystems/robosystems (24 stars, last pushed 3d ago), licensed Apache-2.0. It adds 18 tokens to every session and 1,347 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.