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/gracefullight/docusaurus-plugins/oma-orchestratornpx skills add gracefullight/docusaurus-plugins --skill oma-orchestratorgit clone --depth 1 https://github.com/gracefullight/docusaurus-pluginsWrote 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/gracefullight/docusaurus-plugins/oma-orchestrator)<a href="https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-orchestrator"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-orchestrator.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 | $0.00043 | $0.03175 |
| Opus 5 | $0.00022 | $0.01588 |
| Sonnet 5 | $0.00009 | $0.00635 |
| Haiku 4.5 | $0.00004 | $0.00317 |
Grade A, and why
oma-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 yesterday.
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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestrator - Automated Multi-Agent Coordinator
Scheduling
Goal
Automatically orchestrate multi-agent execution with task decomposition, native/fallback dispatch, memory coordination, progress monitoring, verification, QA cross-review, retry, and result collection.
Intent signature
- User asks to orchestrate, run in parallel, automate multi-agent execution, or coordinate full-stack work end to end.
- Task requires multiple specialist agents and a persistent review/remediation loop.
When to use
- Complex feature requires multiple specialized agents working in parallel
- User wants automated execution without manually spawning agents
- Full-stack implementation spanning backend, frontend, mobile, and QA
- User says "run it automatically", "run in parallel", or similar automation requests
When NOT to use
- Simple single-domain task -> use the specific agent directly
- User wants step-by-step manual control -> use oma-coordination
- Quick bug fixes or minor changes
Expected inputs
- Complex feature or workflow request
- Project config, model/vendor routing, agent types, task constraints, and workspace/session needs
- Acceptance criteria and verification expectations
Expected outputs
- Orchestrator session state, task board, progress files, result files, and final summary
- Specialist agent outputs after mechanical checks, automated verify, and QA cross-review
- Review history and retry/remediation status when loops fail
Dependencies
.agents/oma-config.yaml,.codex/agents/*.toml,.gemini/agents/*.md, or fallbackoma agent:spawn- Memory provider config, subagent prompt template, scripts, task templates, verify script, and session metrics
Control-flow features
- Branches by vendor/native dispatch availability, priority tiers, agent completion/failure, verification status, QA verdict, retry limits, and clarification debt
- Spawns processes/agents and reads/writes memory/result files
- Blocks termination until persistent workflows complete
What ships with it
12 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.
- config/cli-config.yaml 3.0 KB
- resources/memory-schema.md 6.0 KB
- resources/subagent-prompt-template.md 3.8 KB
- scripts/parallel-run.sh 224 B runs code
- scripts/spawn-agent.sh 171 B runs code
- scripts/verify.sh 197 B runs code
- templates/backend-task.md 608 B
- templates/debug-task.md 339 B
- templates/frontend-task.md 598 B
- templates/mobile-task.md 604 B
- templates/qa-task.md 441 B
- templates/tasks-example.yaml 418 B
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.
- yesterday First seen · 311 lines · 43 tokens per session scan A eba6f4494513
oma-orchestrator is a skill published in the GitHub repository gracefullight/docusaurus-plugins (22 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 3,175 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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