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.
npx agentmods add skills/cloudai-x/claude-workflow-v2/parallel-executionnpx skills add CloudAI-X/claude-workflow-v2 --skill parallel-executiongit clone --depth 1 https://github.com/CloudAI-X/claude-workflow-v2Wrote 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/skills/cloudai-x/claude-workflow-v2/parallel-execution)<a href="https://agentmods.dev/skills/cloudai-x/claude-workflow-v2/parallel-execution"><img src="https://agentmods.dev/badge/skills/cloudai-x/claude-workflow-v2/parallel-execution.svg" alt="Measured on agentmods" 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 | $0.00039 | $0.01427 |
| Opus 5 | $0.00019 | $0.00714 |
| Sonnet 5 | $0.00008 | $0.00285 |
| Haiku 4.5 | $0.00004 | $0.00143 |
Grade A, and why
parallel-execution 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 4d 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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Execution Patterns
When to Load
- Trigger: Multi-agent tasks, concurrent operations, spawning subagents, parallelizing independent work
- Skip: Single-step tasks or sequential workflows with no parallelization opportunity
Core Concept
Parallel execution spawns multiple subagents simultaneously using the Task tool with run_in_background: true. This enables N tasks to run concurrently, dramatically reducing total execution time.
Critical Rule: ALL Task calls MUST be in a SINGLE assistant message for true parallelism. If Task calls are in separate messages, they run sequentially.
Execution Protocol
Step 1: Identify Parallelizable Tasks
Before spawning, verify tasks are independent:
- No task depends on another's output
- Tasks target different files or concerns
- Can run simultaneously without conflicts
Step 2: Prepare Dynamic Subagent Prompts
Each subagent receives a custom prompt defining its role:
You are a [ROLE] specialist for this specific task.
Task: [CLEAR DESCRIPTION]
Context:
[RELEVANT CONTEXT ABOUT THE CODEBASE/PROJECT]
Files to work with:
[SPECIFIC FILES OR PATTERNS]
Output format:
[EXPECTED OUTPUT STRUCTURE]
Focus areas:
- [PRIORITY 1]
- [PRIORITY 2]
Step 3: Launch All Tasks in ONE Message
CRITICAL: Make ALL Task calls in the SAME assistant message:
I'm launching N parallel subagents:
[Task 1]
description: "Subagent A - [brief purpose]"
prompt: "[detailed instructions for subagent A]"
run_in_background: true
[Task 2]
description: "Subagent B - [brief purpose]"
prompt: "[detailed instructions for subagent B]"
run_in_background: true
[Task 3]
description: "Subagent C - [brief purpose]"
prompt: "[detailed instructions for subagent C]"
run_in_background: true
Step 4: Retrieve Results with TaskOutput
After launching, retrieve each result:
[Wait for completion, then retrieve]
TaskOutput: task_1_id
TaskOutput: task_2_id
TaskOutput: task_3_id
Step 5: Synthesize Results
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.
- 4d ago First seen · 242 lines · 39 tokens per session scan A 9e9b81908390
parallel-execution is a skill published in the GitHub repository CloudAI-X/claude-workflow-v2 (1,413 stars, last pushed 9d ago), licensed MIT. It adds 39 tokens to every session and 1,427 once invoked, about $0.0002 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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