What did Hlido score srunx?

srunx scored 72/100 (STEADY) in Hlido's independent, hands-on review.

How much does srunx cost?

Hlido recorded the pricing model as: Open source. Derived from evidence Hlido holds, not vendor-supplied; verify current prices on the vendor's pricing page.

Does any vendor pay Hlido for placement?

No. Hlido takes no money from the agents it rates — scoring weights stay private and the evidence behind every verdict is public.

srunx

Name: srunx review
Item: srunx
Rating: 72
Author: Hlido Editor

Infrastructure · tested 2026-08-19 · re-test due 2026-11-19 · by the Hlido desk, not the vendor

In short: A clean, genuinely agent-native toolkit for orchestrating SLURM jobs as code — well-executed and MCP-first, with adoption still the open question.

4 PASS · 0 FAIL of 4 public-surface claims

Visit srunx → scorecard.json

Quick answer

srunx scores 72/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-08-19). STEADY (72) for clean execution, real documentation discipline, and genuine agent-native design (a first-class MCP server, not an afterthought). Pricing: Open source (free entry point documented).

Hlido Editor · 2026-08-19

srunx is the kind of infrastructure tool that respects both its human and its machine users. It turns SLURM job submission — historically a wall of sbatch flags and shell glue — into one-line submits, YAML workflows with depends_on/retry/Jinja templating, matrix parameter sweeps with per-cell tracking, and a web dashboard for the DAG and run history. The part that matters for Hlido's thesis is that it ships an MCP server as a first-class surface: Claude Code and other MCP clients can drive srunx over stdio, including run_workflow with sweeps and transport selection. That's not a bolt-on; it's designed so an agent can own the HPC loop. The documentation is structured and honest (Tutorials / How-to / Reference / Explanation — the Diátaxis discipline), the version is a mature-looking v4.1.1, and the feature list reads like it was built by someone who actually runs jobs on a cluster (Apptainer/Pyxis wiring, ProxyJump-aware rsync, bounded SSH pool). The ceiling is adoption and blast radius: this is a focused open-source project with modest stars, so the risk isn't quality, it's whether it's maintained and battle-tested at your scale. For an ML/HPC team already on SLURM who want agent-drivable orchestration, it's a strong, low-cost bet worth piloting.

Why STEADY

STEADY (72) for clean execution, real documentation discipline, and genuine agent-native design (a first-class MCP server, not an afterthought). Not higher because it's a niche, modestly-adopted open-source project — maturity-at-scale and long-term maintenance are unproven from the public surface. Not FADING because it's actively versioned (v4.1.1) and feature-complete for its stated scope.

Public-surface checklist

PASS Homepage loads (required)
PASS Primary value prop (required) — A clean, genuinely agent-native toolkit for orchestrating SLURM jobs as code — w
PASS Cta present
PASS Evidence or demo — 4 screenshot(s) captured

What we saw

4 screenshots captured by the Hlido engine during the reviewed run (run-224b2a779dbe5b01-ksterx-github-io). Our own captures — not vendor marketing material.

srunx — run screenshot 1 (home.png) — home.png

srunx — run screenshot 2 (page_orchestrate-slurm-jobslike-code.png) — page_orchestrate-slurm-jobslike-code.png

srunx — run screenshot 3 (pagetutorials_installation_.png) — pagetutorials_installation_.png

srunx — run screenshot 4 (pagehow-to_user_guide_.png) — pagehow-to_user_guide_.png

What it does well

One-line SLURM submits with conda/venv/Apptainer/Pyxis wiring handled for you
Workflows as typed YAML with depends_on, retry, and Jinja-templated args — CI-like ergonomics for HPC
First-class MCP server: agents (Claude Code and others) drive srunx over stdio, including sweeps
Parameter sweeps as a matrix cross-product with per-cell tracking and a bounded SSH pool
Documentation follows the Diátaxis structure (Tutorials/How-to/Reference/Explanation) — a real signal of care

What it fails at

Adoption is modest — it's a focused OSS project, so battle-testing at large scale is unproven
SLURM-only by design — no value if your cluster isn't SLURM
Long-term maintenance/bus-factor is unclear from the public surface (single-maintainer risk common to tools this size)
Security/auth posture for the web UI and SSH orchestration isn't detailed on the landing surface

Red flags

Modest adoption footprint (low star count for a v4.x project) — verify maintenance activity and issue-response before depending on it for production runs.

Best for

ML/HPC teams already on SLURM who want job orchestration that reads like code
Agent builders who want an MCP-drivable path to submit and monitor cluster jobs
Researchers running hyperparameter sweeps who want per-cell tracking and a DAG dashboard
Anyone wiring Apptainer/Pyxis containers into SLURM without hand-writing sbatch scripts

Not recommended for

Non-SLURM schedulers (Kubernetes, PBS, LSF) — out of scope
Teams needing a vendor-backed SLA and enterprise support contract
Production-critical pipelines that can't tolerate single-maintainer OSS risk without their own fork/ownership plan

Pricing & access

ModelOpen source
Free entry pointYes — a free tier or open-source edition is documented

Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-08-19.

Compared to

Snakemake agent-drivable-orchestration
Snakemake is the established workflow engine for scientific computing with far larger adoption; srunx is lighter, SLURM-specific, and crucially agent-drivable via MCP. Choose Snakemake for a proven ecosystem, srunx when you want an agent to own the submit/monitor loop.

Agent relevance

CLI MCP SDK Behavioral-testable

Agentic-Commerce Readiness 72/100 · INTEGRABLE

Independent readiness for agent delegation & transaction. How it’s scored · check live

First-class MCP server drivable over stdio (run_workflow with sweep/transport params), plus a Python toolkit and CLI (srunx sbatch ...). Open-source and installable, so an evaluating agent can verify behaviour directly. This is one of the more genuinely agent-native tools in its category.

Agent-friendly score: 8/10

Evidence

Orchestrates SLURM jobs with one-line submits — source (2026-08-19) verified
YAML workflows with depends_on, retry and Jinja templating — source (2026-08-19) verified
Ships an MCP server drivable by Claude Code and other MCP clients over stdio — source (2026-08-19) verified
Parameter sweeps as a matrix cross-product with per-cell tracking — source (2026-08-19) verified
Web UI dashboard for queue, DAG visualization and run history — source (2026-08-19) verified

scorecard.json · transparency passport · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-1+editorial-narrative-v2 · Methodology version 2026.05 · Next review due 2026-11-19

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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