Borrowing it
Nothing to install: this file belongs to gpt-cmdr/ras-commander. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gpt-cmdr/ras-commander/main/.claude/skills/hecras_compute_plans/SKILL.mdgit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWrote 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/skills/gpt-cmdr/ras-commander/hecras_compute_plans)<a href="https://agentmods.dev/skills/gpt-cmdr/ras-commander/hecras_compute_plans"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/hecras_compute_plans/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gpt-cmdr/ras-commander/hecras_compute_plans"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/hecras_compute_plans.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00119 | $0.03074 |
| Opus 5.5 | $0.00048 | $0.01230 |
| Sonnet 5.5 | $0.00024 | $0.00615 |
| Haiku 4.5 | $0.00012 | $0.00307 |
Grade A, and why
hecras_compute_plans 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 25d 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 — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executing HEC-RAS Plans
When the user asks to run HEC-RAS plans, use RasCmdr.compute_plan() for single plans or RasCmdr.compute_parallel() for multiple. Read the primary sources below for complete parameter details.
Primary Sources
1. Execution Patterns (AGENTS.md)
Location: ras_commander/AGENTS.md
Read these sections:
- "Plan Execution" - Core execution methods and parameters
- "Execution Modes" - Four modes: single, parallel, sequential, remote
- "Plan Execution Parameters" - Complete parameter reference
- "Common Workflow Pattern" - Initialize, Execute, Extract
Key execution modes:
# Single plan
RasCmdr.compute_plan("01", dest_folder="run1", num_cores=4)
# Parallel local
RasCmdr.compute_parallel(["01", "02", "03"], max_workers=3)
# Sequential test
RasCmdr.compute_test_mode(["01", "02"])
2. Working Examples (Jupyter Notebooks)
Core execution notebooks:
examples/110_single_plan_execution.ipynb- Complete single plan workflowexamples/111_executing_plan_sets.ipynb- Plan sets and batch processingexamples/112_sequential_plan_execution.ipynb- Test mode executionexamples/113_parallel_execution.ipynb- Parallel execution with performance analysis
Advanced workflows:
examples/500_remote_execution_psexec.ipynb- Distributed execution- Real-time monitoring examples (search for
stream_callbackusage)
3. Code Documentation (Docstrings)
Location: ras_commander/RasCmdr.py
Read these docstrings:
RasCmdr.compute_plan()- Lines 139-250+ (comprehensive parameter docs)RasCmdr.compute_parallel()- Parallel execution detailsRasCmdr.compute_test_mode()- Sequential debugging mode
Callback protocol: ras_commander/callbacks.py
ExecutionCallback- Protocol definitionConsoleCallback,FileLoggerCallback,ProgressBarCallback- Implementations
Quick Reference
Single Plan Execution
Basic pattern:
from ras_commander import init_ras_project, RasCmdr
# Initialize
init_ras_project("path/to/project", "7.0")
# Execute
RasCmdr.compute_plan("01")
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.
- 25d ago Changed 4d8e26cd1040
- 1mo ago First seen · 411 lines · 119 tokens per session scan A 1f110dfe4f1a
hecras_compute_plans is a skill published in the GitHub repository gpt-cmdr/ras-commander (88 stars, last pushed today), licensed MIT. It adds 119 tokens to every session and 3,074 once invoked, about $0.0005 per session on Opus 5.5. 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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