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/dss_read_boundary-data/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/dss_read_boundary-data)<a href="https://agentmods.dev/skills/gpt-cmdr/ras-commander/dss_read_boundary-data"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/dss_read_boundary-data/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/dss_read_boundary-data"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/dss_read_boundary-data.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 | $0.00156 | $0.02460 |
| Opus 5 | $0.00078 | $0.01230 |
| Sonnet 5 | $0.00031 | $0.00492 |
| Haiku 4.5 | $0.00016 | $0.00246 |
Grade A, and why
dss_read_boundary-data 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 9d 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 — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reading DSS Boundary Data
Primary Source Navigator -- Use this skill as a concise entry point to DSS file operations. Read authoritative sources for complete documentation.
Quick Reference
from ras_commander import init_ras_project, RasDss
# Initialize project
ras = init_ras_project("path/to/project", "7.0")
# Read DSS catalog
catalog = RasDss.get_catalog("file.dss")
# Extract single time series
df = RasDss.read_timeseries("file.dss", pathname)
# Extract ALL boundary DSS data (recommended)
enhanced = RasDss.extract_boundary_timeseries(
ras.boundaries_df,
ras_object=ras
)
Primary Sources (Read These First)
1. Module Architecture & Developer Guidance
Location: ras_commander/dss/AGENTS.md
Read this for:
- Lazy loading architecture (no overhead until first use)
- Three-level lazy loading (package → subpackage → method)
- Public API reference table
- DataFrame metadata structure (
df.attrs) - Dependencies (pyjnius, Java, HEC Monolith)
- Adding new DSS methods
- Testing DSS operations
- Common issues and troubleshooting
Why authoritative: Written by maintainers, updated with code changes, read by developers working on the module.
2. Complete Workflow Example
Location: examples/310_dss_boundary_extraction.ipynb
Read this for:
- Step-by-step extraction workflow
- Real project (BaldEagleCrkMulti2D)
- Catalog reading examples
- Single time series extraction
- Batch extraction with
extract_boundary_timeseries() - Plotting DSS boundary data
- Exporting results to CSV
- Accessing extracted DataFrames
Why this is authoritative: Tested with real HEC-RAS projects, serves as functional test, maintained alongside library.
3. Source Code & Docstrings
Location: ras_commander/dss/RasDss.py
Read this for:
- Complete method signatures
- Parameter types and defaults
- Return value structures
- Error handling patterns
- Implementation details
Why this is authoritative: Source code is always correct, docstrings updated with each release.
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.
- 9d ago First seen · 316 lines · 156 tokens per session scan A 8596f420dc8d
dss_read_boundary-data is a skill published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed today), licensed MIT. It adds 156 tokens to every session and 2,460 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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