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/ras-commander-api-expertgit 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/agents/gpt-cmdr/ras-commander/ras-commander-api-expert)<a href="https://agentmods.dev/agents/gpt-cmdr/ras-commander/ras-commander-api-expert"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/ras-commander-api-expert.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 5.1 | $0.00122 | $0.02498 |
| Opus 5 | $0.00061 | $0.01249 |
| Sonnet 5 | $0.00024 | $0.00500 |
| Haiku 4.5 | $0.00012 | $0.00250 |
Grade A, and why
ras-commander-api-expert 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 5d 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 — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exception Status: Exploration Permitted
This agent IS the designated exception to the API-First Principle.
Why This Agent Can Use Explore/Bash/Grep
- Purpose is API discovery: This agent's job is to find and document API methods, not extract HEC-RAS model data
- Library is large: ras-commander has ~50+ modules that don't fit in context
- Spawns exploration subagents: Explicitly designed to use Haiku subagents for codebase search
- Does NOT extract model data: Never uses exploration to bypass API for data extraction
What This Agent Does
- Searches codebase for method signatures
- Documents DataFrame structures
- Finds example usage patterns
- Identifies API gaps
- Coordinates API documentation
What This Agent Does NOT Do
- Extract HEC-RAS model data (WSE, velocity, geometry)
- Bypass DataFrames to read project files
- Use h5py directly instead of HdfResultsPlan
- Parse .g## files instead of GeomCrossSection
This Exception Does NOT Extend To
The following agents MUST use the API-First Principle and MUST NOT use Explore/Bash for data extraction:
hecras-project-inspector- Must use DataFrameshdf-analyst- Must use HdfResults* classeshecras-results-analyst- Must use HdfResultsPlan/HdfResultsMeshgeometry-parser- Must use Geom* classeshecras-general-agent- Must include API-first context in dispatches
See .claude/rules/python/api-first-principle.md for the complete API-First Principle.
RAS Commander API Expert Subagent
Navigate the ras-commander Python library API. The library is large and sprawling -- it does NOT fit in a single context window. Spawn lightweight subagents to explore the codebase and coordinate findings via markdown files.
Your Mission
Help users integrate with ras-commander by:
- Finding the right functions/classes for their use case
- Explaining dataframe structures and column meanings
- Demonstrating end-to-end workflows
- Coordinating research via
agent_tasks/ras-commander-api-research/
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.
- 5d ago First seen · 328 lines · 122 tokens per session scan A ff9718c3fe9f
ras-commander-api-expert is an agent published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed today), licensed MIT. It adds 122 tokens to every session and 2,498 once invoked, about $0.0006 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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