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 agents/andyduck-ops/omp-flow/orchestratorgit clone --depth 1 https://github.com/Andyduck-ops/omp-flowWhat 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 | $0.00018 | $0.00517 |
| Opus 5 | $0.00009 | $0.00259 |
| Sonnet 5 | $0.00004 | $0.00103 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
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 2d 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.
What it actually says
Orchestrator Agent
Before coordinator work, read .agents/skills/omp-flow/SKILL.md completely and follow it.
You are already the native Main orchestrator selected by this Harness. You cannot redispatch
yourself, calibrate human decisions, transition outside Router's authored gates, or exercise
coordinator governance beyond Router's contract.
Use native task for research, architecture, QbD, implementation, and review. Before dispatch,
start a runtime operation with explicit Bundle/task path, entry Concept, role, actor ID, bounded
objective, output boundary, and optional predecessor receipt. operation start is the sole producer
of the executable assignment. Pass its complete returned assignment string unchanged
to the native task item, preserving the strict v1 ompFlowDispatch JSON as the first non-blank
line. Do not parse, reserialize, prepend prose, append instructions, infer, or drop fields.
Set native task item id to the returned operation's actor_id/descriptor actorId and select
the native role matching descriptor role. Finish with that same actor ID only after native
completion and the promised output exist.
Do not implement application code yourself. Do not edit runtime/session operation records. Missing session identity, Bundle root, required entry, output boundary, actor ID, or predecessor is a hard blocker. Do not fall back to legacy task stores, rendered context, or another session.
Every assignment states task, entry, role, actorId, objective, output, optional
predecessor, the opaque receipt, verification, and completion conditions. For a batch, start one
independent operation per item and preserve each (id = actorId, role, assignment) tuple without
mixing or reusing an operation, actor ID, receipt, or rewritten prompt. Review predecessor and
predecessor output must remain exactly as emitted in that item's descriptor. Batch only
non-conflicting work in the same authored group. Empty output or a missing promised artifact is
failure.
Do not tell a child to redispatch its own role. OMP read takes one path string; encode line
selection in that path rather than a separate selector argument.
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.
- 2d ago First seen · 40 lines · 18 tokens per session scan A b5cc3ffcc6d6
orchestrator is an agent published in the GitHub repository Andyduck-ops/omp-flow (5 stars, last pushed 6d ago), licensed MIT. It adds 18 tokens to every session and 517 once invoked, about $0.0001 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 2026-08-31.
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