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 OneWave-AI/claude-skills --skill sub-agent-orchestratorgit clone --depth 1 https://github.com/OneWave-AI/claude-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/onewave-ai/claude-skills/sub-agent-orchestrator)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/sub-agent-orchestrator"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/sub-agent-orchestrator/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/onewave-ai/claude-skills/sub-agent-orchestrator"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/sub-agent-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.00682 |
| Opus 5 | $0.00022 | $0.00341 |
| Sonnet 5 | $0.00009 | $0.00136 |
| Haiku 4.5 | $0.00004 | $0.00068 |
Grade A, and why
sub-agent-orchestrator 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 9d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sub-Agent Orchestrator
Design and execute multi-agent pipelines where each step is a different agent that depends on the previous one. Define roles, dependencies, and handoffs in YAML, then run sequential, parallel, conditional, loop, and map-reduce workflows with retry, timeout, and validation.
Unlike Agent Army (homogeneous parallel code changes) and Agent Swarm (homogeneous parallel data processing), this orchestrator coordinates heterogeneous pipelines where the output of A feeds the input of B.
Contents
references/patterns.md-- The six workflow patterns and the comparison to Agent Army/Swarm.references/workflow-schema.md-- Full YAML workflow definition language.references/examples.md-- Complete worked workflows (research-to-proposal, lead scoring).references/execution-engine.md-- Per-step execution model, retry, timeout, validation, edge cases.references/templates.md-- Reusable workflow scaffolds.references/visual-and-reporting.md-- Text diagrams and the execution report template.
Workflow
-
Determine the mode from the request:
- Run a workflow file: read the YAML at the given path.
- Define and run inline: convert the natural-language description into a workflow YAML (see
references/workflow-schema.md), then show it for approval. - Dry run: parse, validate, resolve inputs, and show the execution plan without deploying agents.
- Inspect: parse the YAML and produce a human-readable description plus a text diagram (see
references/visual-and-reporting.md).
-
Parse and validate the workflow: confirm required fields, that agent IDs resolve, and that there are no circular dependencies. Report syntax or reference errors with the offending line. See
references/execution-engine.md. -
Resolve inputs: collect every required input from the user before starting; apply defaults for optional inputs.
-
Build the execution DAG and run each step in topological order using the matching execution model (sequential, parallel, conditional, loop, map). See
references/execution-engine.md.
What ships with it
6 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.
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.
- 9d ago First seen · 53 lines · 43 tokens per session scan A 955de0cad129
sub-agent-orchestrator is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 682 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 2026-09-03.
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