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 skills add itallstartedwithaidea/agent-skills --skill parallel-agent-orchestrationgit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/parallel-agent-orchestration)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/parallel-agent-orchestration"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/parallel-agent-orchestration/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.
<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/parallel-agent-orchestration"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/parallel-agent-orchestration.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00035 | $0.02698 |
| Opus 5.5 | $0.00014 | $0.01079 |
| Sonnet 5.5 | $0.00007 | $0.00540 |
| Haiku 4.5 | $0.00003 | $0.00270 |
Grade A, and why
parallel-agent-orchestration 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 1mo 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Agent Orchestration
Part of Agent Skills™ by googleadsagent.ai™
Description
Parallel Agent Orchestration is the discipline of dispatching, coordinating, and aggregating results from multiple concurrent subagents to dramatically accelerate complex tasks. Sequential single-agent execution is the default mode for most AI workflows, but it leaves enormous performance on the table. When a task can be decomposed into independent subtasks — analyzing multiple campaigns, reviewing multiple files, searching multiple data sources — parallel dispatch can reduce wall-clock time by 3-10x while maintaining result quality.
This skill encodes the subagent orchestration patterns developed for the Superpowers extension ecosystem and deployed in production at googleadsagent.ai™, where Buddy™ routinely dispatches parallel subagents to analyze different aspects of a Google Ads account simultaneously. One subagent analyzes bidding strategy, another evaluates keyword performance, a third assesses creative quality — all running concurrently. The orchestrator then aggregates their findings into a unified recommendation set, resolving any conflicts between the independent analyses.
The key challenges in parallel orchestration are task partitioning (decomposing the work into truly independent units), result aggregation (combining outputs that may conflict or overlap), resource management (respecting rate limits and cost budgets across parallel agents), and progress monitoring (tracking multiple concurrent streams without losing visibility).
Use When
- A task naturally decomposes into 3+ independent subtasks
- Wall-clock time is a critical constraint (user waiting, SLA requirements)
- Multiple data sources or documents need analysis simultaneously
- Code review spans many files that can be reviewed independently
- Batch operations (migrations, refactoring) across multiple files or services
- You need diverse perspectives on the same problem (ensemble reasoning)
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.
- 1mo ago First seen · 257 lines · 35 tokens per session scan A 836ef7ff91a3
parallel-agent-orchestration is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (44 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 2,698 once invoked, about $0.0001 per session on Opus 5.5. 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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