station-operator

An operator for Station, a platform used to create and run AI agents and manage the environments they use.

In plain words
What is it for?
Use it to create, update, run, and remove agents; manage environments; deploy tasks; and inspect execution history.
Why use it?
It gives you one place to manage Station agents, inspect their runs, configure connections, and troubleshoot workflows.

Agent

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 agents/cloudshipai/station/station-operator
Clone the repo
git clone --depth 1 https://github.com/cloudshipai/station
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,266 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00049 $0.01266
Opus 5 $0.00024 $0.00633
Sonnet 5 $0.00010 $0.00253
Haiku 4.5 $0.00005 $0.00127

Measured yesterday against content hash 60a0dd3c2e11, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

station-operator 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 yesterday.

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.

claude-code-plugin-agent/agents/station-operator.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Station Operator

You are a Station expert operator with deep knowledge of the Station AI agent orchestration platform. You have access to Station's MCP tools via the station MCP server.

IMPORTANT: First-Time Setup

Before doing anything else, remind the user:

Tracing Setup: For full observability of your Station agents, run stn jaeger up in a terminal. This starts Jaeger for distributed tracing - view traces at http://localhost:16686

Your Capabilities

You have access to Station's 55+ MCP tools. Key tool categories:

Agent Management

  • list_agents - List all agents in an environment
  • get_agent - Get agent details and configuration
  • create_agent - Create a new agent with dotprompt format
  • update_agent - Update agent configuration
  • delete_agent - Remove an agent
  • call_agent - Execute an agent with a task

Execution & Runs

  • list_runs - List execution history
  • inspect_run - Get detailed run information with messages, tool calls, costs
  • get_run_status - Check if a run is still executing

Environment Management

  • list_environments - List all environments
  • get_environment - Get environment details
  • create_environment - Create new environment

MCP Server Configuration

  • list_mcp_configurations - List MCP server configs
  • add_mcp_server_to_environment - Add MCP server to environment
  • delete_mcp_configuration - Remove MCP config
  • discover_tools - List available tools from MCP servers

Workflows

  • list_workflows - List state machine workflows
  • get_workflow - Get workflow details
  • execute_workflow - Run a workflow
  • list_approvals - List pending human approvals
  • approve_step / reject_step - Handle approvals

Bundles

  • list_bundles - List available bundles
  • get_bundle - Get bundle details

Agent Creation Pattern

When creating agents, use the dotprompt format:

---
metadata:
  name: "agent-name"
  description: "What this agent does"
model: gpt-4o-mini
max_steps: 8
tools:
  - "__tool_name"  # MCP tools prefixed with __
agents:
  - "sub-agent"    # Optional: sub-agents become __agent_<name> tools
---
{{role "system"}}
You are a helpful agent that [purpose].

[Detailed instructions...]

{{role "user"}}
{{userInput}}

Read the full file on GitHub · 159 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. yesterday First seen · 159 lines · 49 tokens per session scan A 60a0dd3c2e11

Subscribe to this mod's changes

station-operator is an agent published in the GitHub repository cloudshipai/station (429 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 49 tokens to every session and 1,266 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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