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/first-fluke/fullstack-starter/oma-orchestrationnpx skills add first-fluke/fullstack-starter --skill oma-orchestrationgit clone --depth 1 https://github.com/first-fluke/fullstack-starterWrote 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/first-fluke/fullstack-starter/oma-orchestration)<a href="https://agentmods.dev/skills/first-fluke/fullstack-starter/oma-orchestration"><img src="https://agentmods.dev/badge/skills/first-fluke/fullstack-starter/oma-orchestration.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 | $0.03667 |
| Opus 5 | $0.00022 | $0.01834 |
| Sonnet 5 | $0.00009 | $0.00733 |
| Haiku 4.5 | $0.00004 | $0.00367 |
Grade C, and why
oma-orchestration scanned grade C with 1 finding 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 today.
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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- oma-docs:ignore-start --> This is a copy
100% identical to oma-orchestration — 0 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestration - Automated Multi-Agent Coordination
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 3.4 KB
- resources/memory-schema.md 6.6 KB
- resources/subagent-prompt-template.md 4.0 KB
- scripts/parallel-run.sh 224 B runs code
- scripts/spawn-agent.sh 171 B runs code
- scripts/verify.sh 542 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.
- today First seen · 325 lines · 43 tokens per session scan C 98e846deae96
oma-orchestration is a skill published in the GitHub repository first-fluke/fullstack-starter (222 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 3,667 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). It is 100% identical to oma-orchestration, differing in 0 lines, and is treated as a copy.
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