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/hajekim/agentic-design-patterns-extension/parallelizationnpx skills add hajekim/agentic-design-patterns-extension --skill parallelizationgit clone --depth 1 https://github.com/hajekim/agentic-design-patterns-extensionWrote 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/hajekim/agentic-design-patterns-extension/parallelization)<a href="https://agentmods.dev/skills/hajekim/agentic-design-patterns-extension/parallelization"><img src="https://agentmods.dev/badge/skills/hajekim/agentic-design-patterns-extension/parallelization.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 | $0.00373 | $0.02676 |
| Opus 5 | $0.00187 | $0.01338 |
| Sonnet 5 | $0.00075 | $0.00535 |
| Haiku 4.5 | $0.00037 | $0.00268 |
Grade A, and why
parallelization 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 3d 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.
This is a copy
100% identical to parallelization — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallelization Pattern
Overview
The Parallelization Pattern enables multiple components — LLM calls, tool invocations, or entire sub-agents — to execute simultaneously rather than sequentially. By identifying parts of a workflow that are independent of each other, this pattern dramatically reduces total execution time and increases system throughput.
Core Principle: Identify independence — run what doesn't depend on each other at the same time, then synchronize results.
When This Skill Applies
Activate this pattern when:
- Multiple sub-tasks can be performed independently (no data dependency between them)
- External services (APIs, databases) introduce latency that can be overlapped
- The same task must be performed on multiple data items independently
- Throughput and speed are critical system requirements
- A workflow has a natural fan-out (distribute) → fan-in (aggregate) structure
Rule of thumb: If Step B doesn't need Step A's output to begin, run them simultaneously.
DEFINE → PLAN → ACTION Workflow
DEFINE
Identify the parallelism opportunities:
- Which sub-tasks have no data dependency on each other?
- Which steps interact with external services (API calls, database queries, searches)?
- Where does the workflow have a natural fan-out structure?
- What synchronization point (fan-in) collects all parallel results?
PLAN
Design the parallel architecture:
- Map the dependency graph — which nodes can run concurrently?
- Define the fan-out: distribute tasks to parallel workers/agents
- Define the fan-in: collect and aggregate results from all parallel branches
- Identify which subsequent steps are sequential (depend on aggregated results)
- Plan error handling: what happens if one parallel branch fails?
ACTION
Implement parallel execution:
- Use async/await, threading, or framework-native parallel execution primitives
- Launch all independent tasks concurrently
- Use synchronization primitives (gather, join, await all) to collect results
- Pass aggregated results to the sequential continuation step
- Monitor and handle partial failures gracefully
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.
- 3d ago First seen · 299 lines · 373 tokens per session scan A d0458d7c03dd
parallelization is a skill published in the GitHub repository hajekim/agentic-design-patterns-extension (1 stars, last pushed 5mo ago), licensed MIT. It adds 373 tokens to every session and 2,676 once invoked, about $0.0019 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to parallelization, differing in 3 lines, and is treated as a copy.
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