orchestrate-julia-workloads

orchestrate-julia-workloads is a skill for Codex from Krastanov/JuliaLLMAgentSkills. It costs 64 tokens per session (343 once invoked), scanned A, original, Unlicense.

A guide to coordinating concurrent work in Julia using tasks, channels, threads, external library workers, and separate processes. It covers both overlapping input/output work and parallel CPU work.

In plain words
What is it for?
Use it for producer-consumer pipelines, bounded work queues, threaded calculations, thread settings for BLAS or FFT libraries, and running external commands from Julia.
Why use it?
It helps prevent common concurrency problems such as races, deadlocks, failed child work being ignored, and using more workers than the computer can handle.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it for producer-consumer pipelines, bounded work queues, threaded calculations, thread settings for BLAS or FFT libraries, and running external commands from Julia.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/krastanov/juliallmagentskills/orchestrate-julia-workloads
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Krastanov/JuliaLLMAgentSkills --skill orchestrate-julia-workloads
Clone the repo
git clone --depth 1 https://github.com/Krastanov/JuliaLLMAgentSkills

Made for: Codex.

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 orchestrate-julia-workloads

README.md
[![agentmods](https://agentmods.dev/badge/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads/github.svg)](https://agentmods.dev/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads)
Your own site
<a href="https://agentmods.dev/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads"><img src="https://agentmods.dev/badge/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads/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.

agentmods 80×15 button for orchestrate-julia-workloads

Your own site · 80×15
<a href="https://agentmods.dev/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads"><img src="https://agentmods.dev/badge/skills/krastanov/juliallmagentskills/orchestrate-julia-workloads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 343 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00064 $0.00343
Opus 5 $0.00032 $0.00171
Sonnet 5 $0.00013 $0.00069
Haiku 4.5 $0.00006 $0.00034

Measured 11d ago against content hash 226e2303e33f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

orchestrate-julia-workloads 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 11d 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.

orchestrate-julia-workloads/SKILL.md · 26 lines

What it actually says

Orchestrate Julia Workloads

Choose the smallest execution model that matches the work, then make task and process lifetimes explicit.

Route the Work

Core Rules

  1. Keep a correct sequential implementation or test oracle.
  2. Bound concurrency and buffering from resource limits, not only input size.
  3. Enclose child work in a scope that waits and propagates failures.
  4. Give each task ownership of mutable state; synchronize truly shared state.
  5. Avoid stacking Julia threads, library threads, and process workers without measuring the total resource use.
  6. Test success, failure, cancellation or interruption, empty input, and constrained concurrency.
  7. Measure representative workloads before retaining a parallel implementation.
Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 26 lines · 64 tokens per session scan A 226e2303e33f

Subscribe to this mod's changes

orchestrate-julia-workloads is a skill published in the GitHub repository Krastanov/JuliaLLMAgentSkills (30 stars, last pushed 1mo ago), licensed Unlicense. It adds 64 tokens to every session and 343 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens