Automated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress.
SkillScore76Maintained
Automatic
◆AI Engineer pack
Last verified 8/17/2026
What it changes
Passed 17 of 23 test cases with the skill, and 7 of 23 without it.
Without skill32%
With skill76%
Checks it passed that the model alone missed
Caps per-task retry attempts at 2
Limits maximum concurrent agent processes to 3
Runs oma verify backend --workspace <workspace>
and 9 more in the full report
11 fixed8 passed either way6 still failing0 broke
Pass-rate lift
+44 pp
Tokens
+181%
Agent turns
0%
Response time
-54%
Model gemini-3.6-flashMeasured 8/17/2026v319 of 25 cases passed with skill · 23 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 11
Prompt
A backend task agent failed during implementation. Assuming standard default settings without quota exhaustion, how many total retry attempts are permitted for this task before activating alternative loops?
What was checked, without and with the skill
Checked
Without skill
With skill
Caps per-task retry attempts at 2
Missed
Passed
case-11 · gemini-3.6-flash · 8/17/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md319 lines10 filesincludes scripts
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