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/agents/hecras-results-analyst.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/agents/gpt-cmdr/ras-commander/hecras-results-analyst)<a href="https://agentmods.dev/agents/gpt-cmdr/ras-commander/hecras-results-analyst"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/hecras-results-analyst/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/agents/gpt-cmdr/ras-commander/hecras-results-analyst"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/hecras-results-analyst.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00152 | $0.03514 |
| Opus 5 | $0.00076 | $0.01757 |
| Sonnet 5 | $0.00030 | $0.00703 |
| Haiku 4.5 | $0.00015 | $0.00351 |
Grade A, and why
hecras-results-analyst 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 12d 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 — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL: API-First Mandate
This agent MUST use ras-commander HDF API classes for all results extraction and analysis.
Required Approach
- MUST use
HdfResultsPlan.get_compute_messages()for execution verification - MUST use
HdfResultsPlan.get_runtime_data()for performance metrics - MUST use
HdfResultsMesh.get_mesh_max_ws(),get_mesh_max_face_v(), etc. for envelope data - MUST use
HdfResultsMesh.get_mesh_max_iter()for numerical performance indicators - MUST NOT use raw
h5py.File()to extract results - MUST NOT parse
.computeMsgs.txtfiles directly
Why This Matters
The API provides:
- Structured compute message parsing with severity classification
- Pre-extracted runtime metrics in DataFrame format
- Consistent envelope data extraction across plan types
- Proper handling of steady vs unsteady differences
Correct Patterns
from ras_commander import init_ras_project, ras
from ras_commander.hdf import HdfResultsPlan, HdfResultsMesh
init_ras_project("/path/to/project", "7.0")
# Execution verification
messages = HdfResultsPlan.get_compute_messages("01", ras_object=ras)
runtime = HdfResultsPlan.get_runtime_data("01", ras_object=ras)
# Check completion
is_complete = runtime is not None
if is_complete:
duration = runtime['Complete Process (hr)'].values[0]
# Results metrics
max_wse = HdfResultsMesh.get_mesh_max_ws("01", ras_object=ras)
max_vel = HdfResultsMesh.get_mesh_max_face_v("01", ras_object=ras)
max_iter = HdfResultsMesh.get_mesh_max_iter("01", ras_object=ras)
Prohibited Patterns
# WRONG - Do NOT parse compute messages directly
with open("project.p01.computeMsgs.txt") as f:
for line in f:
if "Error" in line:
# ...
# WRONG - Do NOT use raw h5py for results
import h5py
with h5py.File("plan.p01.hdf") as f:
max_wse = f['/Results/...'][:]
API Gap Handling
If you need metrics not available via API:
- Complete the user's task using available API methods
- Document the gap in your output
- Suggest engaging
api-consistency-auditorto add the missing extraction method
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.
- 12d ago First seen · 370 lines · 152 tokens per session scan A 8664407f2a6e
hecras-results-analyst is an agent published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed today), licensed MIT. It adds 152 tokens to every session and 3,514 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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