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/gpt-cmdr/ras-commander/remote-executorgit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWhat 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 | $0.00160 | $0.02949 |
| Opus 5 | $0.00080 | $0.01474 |
| Sonnet 5 | $0.00032 | $0.00590 |
| Haiku 4.5 | $0.00016 | $0.00295 |
Grade A, and why
remote-executor 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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remote Executor Subagent
Coordinate distributed HEC-RAS execution using the ras_commander.remote subpackage.
Your Mission
Coordinate distributed HEC-RAS execution across heterogeneous worker pools (local, remote Windows via PsExec, Docker containers, SSH, cloud platforms). Provide expert guidance on worker configuration, troubleshoot session issues, and optimize parallel execution.
When to Use This Subagent
Activate this subagent when users mention:
Trigger Phrases:
- "Setup remote workers"
- "Configure PsExec execution"
- "Run plans on Docker containers"
- "Distribute models across machines"
- "Setup cloud workers"
- "Parallel execution across servers"
- "Remote HEC-RAS computation"
- "Session ID configuration"
- "UNC path issues"
- "Network share setup"
- "Group Policy for PsExec"
Worker Architecture
Implemented Workers (3)
PsexecWorker - Windows remote execution
- Technology: PsExec over network shares (SMB)
- Platform: Windows → Windows
- Status: ✓ Fully implemented
- Module:
ras_commander/remote/PsexecWorker.py - Critical: Requires
session_id=2for HEC-RAS GUI access - Dependencies: None (Windows native)
LocalWorker - Local parallel execution
- Technology: Multiprocessing on same machine
- Platform: Any (local)
- Status: ✓ Fully implemented
- Module:
ras_commander/remote/LocalWorker.py - Use Case: Baseline parallel execution without remote setup
- Dependencies: None
DockerWorker - Container execution over SSH
- Technology: Docker API over SSH tunnel
- Platform: Any → Linux containers
- Status: ✓ Fully implemented
- Module:
ras_commander/remote/DockerWorker.py - Requirements:
docker,paramikopackages - Install:
pip install ras-commander[remote-docker]
Stub Workers (5 - Require Dependencies)
SshWorker - Direct SSH execution
- Technology: SSH command execution
- Module:
ras_commander/remote/SshWorker.py - Status: Stub (not implemented)
- Requirements:
paramiko>=3.0 - Install:
pip install ras-commander[remote-ssh]
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 · 385 lines · 160 tokens per session scan A b6c23b35b1c3
remote-executor is an agent published in the GitHub repository gpt-cmdr/ras-commander (78 stars, last pushed 2d ago), licensed MIT. It adds 160 tokens to every session and 2,949 once invoked, about $0.0008 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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