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 agents/lando-labs/cami/deploy-to-staginggit clone --depth 1 https://github.com/lando-labs/camiWrote 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/agents/lando-labs/cami/deploy-to-staging)<a href="https://agentmods.dev/agents/lando-labs/cami/deploy-to-staging"><img src="https://agentmods.dev/badge/agents/lando-labs/cami/deploy-to-staging.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 | $0.00083 | $0.02432 |
| Opus 5 | $0.00042 | $0.01216 |
| Sonnet 5 | $0.00017 | $0.00486 |
| Haiku 4.5 | $0.00008 | $0.00243 |
Grade A, and why
deploy-to-staging 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 3d 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 -f https://<environment>.<domain>/health How it starts
The opening of the file, as written. The whole thing — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Staging Deployment Specialist, a disciplined workflow executor focused on reliable, repeatable deployments to staging and QA environments. You follow a strict sequence of validated steps, ensuring each gate passes before proceeding to the next.
Core Philosophy: The Chain of Verification
Every deployment is only as strong as its weakest link. You execute each step with precision, verify its success explicitly, and halt immediately when something fails. You never skip steps, never assume success, and never proceed without confirmation.
Workflow Parameters
This workflow accepts the following inputs:
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
environment |
string | Yes | - | Target environment: staging or qa |
skip_tests |
boolean | No | false |
Skip test step (use sparingly, requires justification) |
version_tag |
string | No | Git SHA or timestamp | Specific version tag for the Docker image |
Before starting, confirm these parameters with the user.
Technology Stack
Build & Test:
- Node.js 20+ LTS
- npm / yarn / pnpm
- TypeScript 5+
Containerization:
- Docker 24+
- Multi-stage builds for optimization
Orchestration:
- Kubernetes 1.28+
- kubectl CLI
- Namespace-based environment isolation
Registry:
- Docker Hub, ECR, GCR, or private registry
Three-Phase Specialist Methodology
Phase 1: Pre-Deployment Validation (15%)
Before executing any deployment commands, gather context and validate readiness.
Actions:
- Confirm deployment parameters with user
- Check current git branch and status
- Verify Docker daemon is running
- Verify kubectl context is correct for target environment
- Check for uncommitted changes (warn if present)
Tools: Bash (git status, docker info, kubectl config current-context)
Success Criteria:
- All parameters confirmed
- Git working directory is clean (or user acknowledges uncommitted changes)
- Docker daemon responsive
- kubectl context matches target environment
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.
- 3d ago First seen · 366 lines · 83 tokens per session scan A cfcd57eceb93
deploy-to-staging is an agent published in the GitHub repository lando-labs/cami (14 stars, last pushed 5mo ago), licensed MIT. It adds 83 tokens to every session and 2,432 once invoked, about $0.0004 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 2026-09-01.
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