Parallel Batch Operations
QwenLM/qwen-code
Runs one operation across many files with parallel worker agents: finds files by glob pattern, splits them into chunks, launches workers and summarizes the results.
Parallel processing with joblib for grid search and batch computations.
Apache-2.0Auto-check passed
Install Parallel Processing
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench parallel-processing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .claude/skills/parallel-processing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .claude/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench parallel-processing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .agents/skills/parallel-processing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .agents/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench parallel-processing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .cursor/skills/parallel-processing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .cursor/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/benchflow-ai/skillsbench.git --path tasks/mars-clouds-clustering/environment/skills/parallel-processing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench parallel-processing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .gemini/skills/parallel-processing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .gemini/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install benchflow-ai/skillsbench parallel-processingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .github/skills/parallel-processing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .github/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add benchflow-ai/skillsbench --skill parallel-processing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/skillsbench parallel-processing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks/mars-clouds-clustering/environment/skills/parallel-processing .opencode/skills/parallel-processing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "parallel-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/mars-clouds-clustering/environment/skills/parallel-processing into .opencode/skills/parallel-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parallel-processing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
parallel-processing- GitHub stars
- 1.8k
- Token cost
- ~511 tokens
- SKILL.md length
- 89 words
- Files
- 1
- Skills in repo
- 178
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Parallel processing with joblib for grid search and batch computations.
- Speeding up computationally intensive tasks across multiple CPU cores
- SKILL.md covers Basic Usage, Key Parameters, Grid Search Example and Pre-computing Shared Data, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Parallel Processing is an agent skill from benchflow-ai/skillsbench. Parallel processing with joblib for grid search and batch computations. Use when speeding up computationally intensive tasks across multiple CPU cores.
Its SKILL.md is about 510 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is Apache-2.0.
When your agent uses it
- Speeding up computationally intensive tasks across multiple CPU cores
Example prompts
- “/parallel-processing”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Parallel Processing loads about 511 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 89 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 89 words, ~511 tokens.
Download SKILL.mdSave it as
.claude/skills/parallel-processing/SKILL.md (or your agent's skills folder).- name
- parallel-processing
- description
- Parallel processing with joblib for grid search and batch computations. Use when speeding up computationally intensive tasks across multiple CPU cores.
Parallel Processing with joblib
Speed up computationally intensive tasks by distributing work across multiple CPU cores.
Basic Usage
from joblib import Parallel, delayed
def process_item(x):
"""Process a single item."""
return x ** 2
# Sequential
results = [process_item(x) for x in range(100)]
# Parallel (uses all available cores)
results = Parallel(n_jobs=-1)(
delayed(process_item)(x) for x in range(100)
)Key Parameters
- n_jobs:
-1for all cores,1for sequential, or specific number - verbose:
0(silent),10(progress),50(detailed) - backend:
'loky'(CPU-bound, default) or'threading'(I/O-bound)
Grid Search Example
from joblib import Parallel, delayed
from itertools import product
def evaluate_params(param_a, param_b):
"""Evaluate one parameter combination."""
score = expensive_computation(param_a, param_b)
return {'param_a': param_a, 'param_b': param_b, 'score': score}
# Define parameter grid
params = list(product([0.1, 0.5, 1.0], [10, 20, 30]))
# Parallel grid search
results = Parallel(n_jobs=-1, verbose=10)(
delayed(evaluate_params)(a, b) for a, b in params
)
# Filter results
results = [r for r in results if r is not None]
best = max(results, key=lambda x: x['score'])Pre-computing Shared Data
When all tasks need the same data, pre-compute it once:
# Pre-compute once
shared_data = load_data()
def process_with_shared(params, data):
return compute(params, data)
# Pass shared data to each task
results = Parallel(n_jobs=-1)(
delayed(process_with_shared)(p, shared_data)
for p in param_list
)Performance Tips
- Only worth it for tasks taking >0.1s per item (overhead cost)
- Watch memory usage - each worker gets a copy of data
- Use
verbose=10to monitor progress
© benchflow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in tasks/mars-clouds-clustering/environment/skills/parallel-processing of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Compare with similar skills
Parallel Processing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Parallel Processing this skillbenchflow-ai/skillsbench | 1.8k | — | ~511 | Automated safety check: Pass | Apache-2.0 | |
| Parallel Batch OperationsQwenLM/qwen-code | 28k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Batchasgeirtj/system_prompts_leaks | 69k | — | ~1.3k | Automated safety check: Pass | CC0-1.0 | |
| Bio Batch ProcessingFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~2.2k | Automated safety check: Pass | None | |
| Processing API Batchesjeremylongshore/tons-of-skills-marketplace | 2.8k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Processing Computer Vision Tasksjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~898 | Automated safety check: Pass | MIT |
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Questions about Parallel Processing
What does Parallel Processing do?
Parallel processing with joblib for grid search and batch computations. Parallel Processing is an agent skill from benchflow-ai/skillsbench. Parallel processing with joblib for grid search and batch computations.
When should I use Parallel Processing?
Parallel Processing fits situations like: speeding up computationally intensive tasks across multiple CPU cores.
How do I install Parallel Processing in Claude Code?
Run `npx skills add benchflow-ai/skillsbench --skill parallel-processing -a claude-code`. Or copy the skill folder (tasks/mars-clouds-clustering/environment/skills/parallel-processing in benchflow-ai/skillsbench) into .claude/skills/parallel-processing in your project. Claude Code loads it when a task matches its description.
How do I install Parallel Processing in Codex?
Run `npx skills add benchflow-ai/skillsbench --skill parallel-processing -a codex`. Or copy the skill folder (tasks/mars-clouds-clustering/environment/skills/parallel-processing in benchflow-ai/skillsbench) into .agents/skills/parallel-processing in your project. Codex loads it when a task matches its description.
Can I use Parallel Processing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill parallel-processing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/parallel-processing, .gemini/skills/parallel-processing, .github/skills/parallel-processing and .opencode/skills/parallel-processing in your project.
What does Parallel Processing need to run?
SKILL.md names no scripts, command-line tools or credentials: Parallel Processing is instructions for the agent only. Our summary lists: Python 3.
Does Parallel Processing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Parallel Processing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Parallel Processing use?
Parallel Processing is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Parallel Processing use?
About 511 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Parallel Processing?
Skills that share tags, products or a category with Parallel Processing: Parallel Batch Operations (QwenLM/qwen-code, 28k stars), Batch (asgeirtj/system_prompts_leaks, 69k stars), Bio Batch Processing (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars) and Processing API Batches (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Parallel Processing?
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,832 GitHub stars. The repository holds 178 skills in this directory. The repository was last updated on July 23, 2026.
Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.