data-workflows: Skill for Claude Code

.claude/skills/armada-pipeline/SKILL.md

armada-pipeline is a skill for Claude Code from boettiger-lab/data-workflows. It costs 107 tokens per session (3,498 once invoked), scanned A, original, BSD-3-Clause.

A guide to running many batch jobs through Armada, a queueing system on the Nautilus Research Platform. It covers shell login, command-line setup, queue mapping, priorities, and splitting work into small pieces.

In plain words
What is it for?
Use it to configure Armada, choose suitable priorities, map queues to namespaces, and decide when to split a large batch into thousands of smaller jobs.
Why use it?
It helps avoid slow scheduling and wasted work when large Kubernetes jobs wait for enough memory or are interrupted. Small pieces reduce how much work is lost and fit into more available capacity.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is boettiger-lab/data-workflows's own configuration. It tells Claude Code how to work on data-workflows itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything data-workflows configures →

Reuse

Borrowing it

Nothing to install: this file belongs to boettiger-lab/data-workflows. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/boettiger-lab/data-workflows/main/.claude/skills/armada-pipeline/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/boettiger-lab/data-workflows

Made for: Claude Code.

Wrote 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.

agentmods badge for armada-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/boettiger-lab/data-workflows/armada-pipeline.svg)](https://agentmods.dev/skills/boettiger-lab/data-workflows/armada-pipeline)
Your own site
<a href="https://agentmods.dev/skills/boettiger-lab/data-workflows/armada-pipeline"><img src="https://agentmods.dev/badge/skills/boettiger-lab/data-workflows/armada-pipeline.svg" alt="Measured on agentmods" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,498 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 6 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Supply Chain · line 85
    Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.
    Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
  • high Privilege Escalation · line 102
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Supply Chain · line 126
    Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.
    Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
  • medium Data Exfiltration · line 85
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Rogue Agent · line 95
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Tool Misuse · line 177
    Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.
    Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00107 $0.03498
Opus 5 $0.00053 $0.01749
Sonnet 5 $0.00021 $0.00700
Haiku 4.5 $0.00011 $0.00350

Measured 7d ago against content hash 628b90075601, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

armada-pipeline scanned grade A with 1 finding 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 7d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST "https://authentik.nrp-nautilus.io/application/o/device/" \
.claude/skills/armada-pipeline/SKILL.md · 292 lines

How it starts

The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Armada Pipeline (NRP)

Why Armada: microslicing, not requeueing

Armada's value is not automatic retry — the NRP docs state plainly that "preempted jobs will not be automatically rescheduled". Reaching for Armada to survive preemption is the wrong reason.

The real reason is that Armada is not bound by the k8s indexed-Job completion cap (~200, an etcd pressure limit). Millions of completions are fine. That makes microslicing practical, and microslicing improves four things at once:

few large jobs many small slices
unit of loss on preemption hours minutes
RAM requested sized for the worst step in the chain what each step actually needs
scheduling needs large contiguous free slots; pods sit Pending fits in scraps almost anywhere
stragglers one holds up the batch and can leave stale output retries invisibly

The scheduling point is the one most easily missed: 20 pods at 64Gi need ~1.3 TB free in large contiguous chunks, so realized parallelism is far below requested. Thousands of 8-16Gi slices pack into whatever is free and start immediately. Placing 10,000 small slices is often faster than placing 100 big ones — more so under preemption.

Big jobs also make you conservative: a 35-step chain must request the peak requirement of its worst step, so every step pays that cost. One unit per job asks for what it needs.

⛔ Authentication: use the device-code flow, not the documented PKCE flow

The config NRP publishes at https://nrp.ai/.armadactl.yaml uses PKCE (openIdAuth), which binds 127.0.0.1:50000 and waits for a browser redirect. This cannot complete in a headless shell. It hangs silently, prints no URL, and — critically — keeps holding port 50000, so every later attempt dies with:

panic: listen tcp 127.0.0.1:50000: bind: address already in use

That panic is a symptom of the first hung process, not a separate fault. Kill the original before retrying.

Read the full file on GitHub · 292 lines

Changes

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.

  1. 7d ago First seen · 292 lines · 107 tokens per session scan A 628b90075601

Subscribe to this mod's changes

armada-pipeline is a skill published in the GitHub repository boettiger-lab/data-workflows (5 stars, last pushed 2d ago), licensed BSD-3-Clause. It adds 107 tokens to every session and 3,498 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

latchbio-integration

Build, register, debug, and operate bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and…

K-Dense-AI/scientific-agent-skills · 76 tokens

modal-compute

Run explicitly chosen research benchmark or replication jobs on Modal's serverless infrastructure. Use when a Feynman research workflow needs burst remote GPU compute and the Modal CLI is available.

companion-inc/feynman · 39 tokens

remote-compute-ssh

Evaluate and use SSH Remote Compute before choosing where to run GPU, high-memory, parallel, batch, model-inference, bioinformatics, or other long-running scientific work; supports short remote commands and asynchronous jobs with automatic harvest and analysis.

aipoch/open-science · 53 tokens

dnanexus-integration

DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.

synthetic-sciences/openscience · 49 tokens

latchbio-integration

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

synthetic-sciences/openscience · 45 tokens

modal-serverless-gpu

Run approved CPU or GPU work through OpenScience computejob on the user's configured Modal account. Use for isolated scientific scripts, dependency provisioning, durable outputs, logs, status, cancellation, and recovery. Never invoke the Modal SDK or CLI directly.

synthetic-sciences/openscience · 54 tokens