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/python-environment-managergit 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 | $0.00130 | $0.03868 |
| Opus 5 | $0.00065 | $0.01934 |
| Sonnet 5 | $0.00026 | $0.00774 |
| Haiku 4.5 | $0.00013 | $0.00387 |
Grade C, and why
python-environment-manager scanned grade C with 2 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
| uv | Windows: `irm https://astral.sh/uv/install.ps1 \| iex`<br>Mac/Linux: `curl -LsSf https://astral.sh/uv/install.sh \| sh` | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| uv | Windows: `irm https://astral.sh/uv/install.ps1 \| iex`<br>Mac/Linux: `curl -LsSf https://astral.sh/uv/install.sh \| sh` | How it starts
The opening of the file, as written. The whole thing — 510 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Environment Manager
Set up and manage ras-commander Python environments. Handle environment creation, validation, troubleshooting, and upgrades.
Key Decision: No Editable Install for Development
CRITICAL: The rascmdr_local environment does NOT use pip install -e .
Instead, use a toggle cell in Jupyter notebooks that manipulates sys.path to load local source code. This approach:
- Guarantees local source is always loaded (even if pip package exists)
- Remains simple to understand and explain
- Works reliably across all environments
- Can be toggled with a single variable
Why sys.path.insert(0, ...) Works
Python searches sys.path in order (index 0 first). By inserting the local repo path at position 0:
- Python finds
ras_commander/in the repo first - The pip-installed package (if any) is never reached
- 100% guaranteed local source loading
Standard Environment Names
RasCommander (User Environment)
Purpose: Standard user environment with pip package
When to use:
- Running example notebooks as an end user
- Using ras-commander for HEC-RAS automation
- NOT editing ras-commander source code
Setup:
conda create -n RasCommander python=3.13
conda activate RasCommander
pip install ras-commander
pip install jupyter ipykernel
python -m ipykernel install --user --name RasCommander --display-name "Python (RasCommander)"
rascmdr_local (Development Environment)
Purpose: Development environment with dependencies only (NO ras-commander pip install)
When to use:
- Editing ras-commander source code
- Contributing to the library
- Testing code changes immediately
Setup:
conda create -n rascmdr_local python=3.13
conda activate rascmdr_local
# Install DEPENDENCIES ONLY - NOT ras-commander itself
pip install h5py numpy pandas geopandas matplotlib shapely scipy xarray tqdm requests rasterstats rtree pyproj fiona
# Install Jupyter
pip install jupyter ipykernel
python -m ipykernel install --user --name rascmdr_local --display-name "Python (rascmdr_local)"
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.
- yesterday First seen · 510 lines · 130 tokens per session scan C 9a950886659b
python-environment-manager is an agent published in the GitHub repository gpt-cmdr/ras-commander (78 stars, last pushed yesterday), licensed MIT. It adds 130 tokens to every session and 3,868 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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