Agent skill · Workflow & Productivity

hecras_parse_compute-messages

Parse HEC-RAS compute output from HDF files to extract execution status, diagnostic messages, and performance metrics. Converts raw computation messages into structured diagnostics for workflow orchestration. Use when checking plan completion status, extracting compute messages, diagnosing execution failures, analyzing runtime performance, or interpreting HEC-RAS error codes. performance, error diagnostics, HEC-RAS output, simulation results, warnings, convergence, instability, time step, iteration.

majiayu000github.com/majiayu000GitHub ↗
claude-coderead-onlyMIT
Install
npx skills add majiayu000/claude-skill-registry --skill hecras-parse-compute-messages --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 11 KB
Bundled scripts: none
Allowed tools: ReadGrepGlob
Path: skills/analysis/hecras-parse-compute-messages/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Parsing HEC-RAS Compute Messages **Primary Sources (navigate to these for complete details)**: - **HDF Class Reference**: `ras_commander/hdf/AGENTS.md` - Class hierarchy, decorators - **HdfResultsPlan Implementation**: `ras_commander/hdf/HdfResultsPlan.py` - Compute message methods - **Working Example**: `examples/400_1d_hdf_data_extraction.ipynb` - Compute message extraction This skill provides patterns for extracting and interpreting HEC-RAS computation output. For implementation details, see the primary sources above. --- ## Quick Start ### Check Plan Completion and Extract Messages ```python from ras_commander import init_ras_project, HdfResultsPlan # Initialize project init_ras_project("C:/Projects/MyModel", "6.6") # Extract compute messages (handles HDF + .txt fallback automatically) messages = HdfResultsPlan.get_compute_messages("01") # Check if plan has results (runtime data exists only for completed plans) runtime = HdfResultsPlan.get_runtime_data("01") is_complete = runtime is not None if is_complete: print(f"Plan completed in {runtime['Complete Process (hr)'].values[0]:.2f} hours") else: print("Plan has not been executed or did not complete") ``` --- ## API Reference #

What's inside
Steps it walks through
  1. Quick Start
  2. Check Plan Completion and Extract Messages
  3. API Reference
  4. HdfResultsPlan.getcomputemessages()
  5. HdfResultsPlan.getcomputemessageshdfonly()
  6. HdfResultsPlan.getruntimedata()
  7. Common Error Patterns
  8. Critical Errors (Plan Failed)
  9. Stability Warnings (Plan May Succeed)
  10. Informational Messages
  11. Message Parsing Pattern
  12. Basic Severity Classification
  13. Extract Structured Diagnostics
  14. Output Schema for Orchestrators
Ships with 1 file
  • metadata.json
More from claude-skill-registry
All skills →
About this skill
What does the hecras_parse_compute-messages skill do?

Parse HEC-RAS compute output from HDF files to extract execution status, diagnostic messages, and performance metrics. Converts raw computation messages into structured diagnostics for workflow orchestration. Use when checking plan completion status, extracting compute messages, diagnosing execution failures, analyzing runtime performance, or interpreting HEC-RAS error codes. performance, error diagnostics, HEC-RAS output, simulation results, warnings, convergence, instability, time step, iteration.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill hecras-parse-compute-messages --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going