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/andyduck-ops/omp-flow/omp-flow-executenpx skills add Andyduck-ops/omp-flow --skill omp-flow-executegit 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 | $0.00025 | $0.01029 |
| Opus 5 | $0.00013 | $0.00515 |
| Sonnet 5 | $0.00005 | $0.00206 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
omp-flow-execute 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OMP-Flow Execute
Implementation Loop
- Read
work/index.mdor the Bundle links that communicate the accepted work grouping. - Select work whose prerequisites are semantically satisfied. Parallelize only an authored group whose code/output scopes do not conflict.
- Start each operation with explicit
task, workentry, implementerrole,actor-id, boundedobjective, handoff/codeoutput, and any relevantpredecessor. - Dispatch the native
executor/omp-flow-implementrole with the completeassignmentstring returned by thatoperation start, exactly unchanged. Keep its strict v1ompFlowDispatchJSON as the first non-blank line; do not parse, reserialize, prepend, append, infer, or drop fields. Set native itemidto the returned operation'sactor_id/descriptoractorId, and keep the item role equal to descriptorrole. - Require the Implementer to inspect existing patterns, stay in scope, run work verification, and write or update the promised linked handoff Concept.
- Finish the operation with the same actor ID only after the native result and promised output exist. A failure remains a visible failed operation and does not manufacture semantic status.
Independent Review Loop
- Start a fresh review operation with the same work Concept as entry, an independent reviewer actor ID, a descriptive Review Concept output, and the completed implementation receipt as predecessor.
- Forward that review operation's returned assignment unchanged with native item
id = actor_id = actorIdand matching reviewer role. Its descriptor carries the predecessor receipt and predecessor output; do not reconstruct or remove either. - Runtime correlation must reject a reviewer who is the implementation actor or whose predecessor is not completed.
- Reviewer follows the work Concept to its handoff, inspects the real changed code and design, runs independent checks, and writes the promised Review Concept.
- Finish with the same reviewer actor ID. Read the review's findings and verdict as knowledge; Python does not parse or duplicate them into Evidence or row status.
- Classify every finding with all applicable labels:
HARD_BLOCKERviolates a non-negotiable safety, authority, identity, integrity, assignment/receipt/source-binding, or irreversible-effect boundary;PRINCIPAL_BLOCKERconcretely prevents the next authored principal product checkpoint;WORK_FAILviolates the bounded Work's own acceptance criteria or a test that exercises them; it may overlap either stronger label;ADVISORYis any other recorded quality, robustness, completeness, or elegance risk. A failed prerequisite Work required by the next principal checkpoint is alsoPRINCIPAL_BLOCKER.HARD_BLOCKERandPRINCIPAL_BLOCKERpause the principal path and return to the owning work/design Concept for explicit routing.WORK_FAILmakes that WorkFAILand enters a recorded owning-Work backlog; absent a hard/principal label it must not autonomously create repair/review work, reopen accepted Work, or preempt the principal checkpoint.ADVISORYremains recorded residual risk and has none of those effects.
- A hard/principal failure requires explicit human/design routing. When the principal checkpoint
produces
continue,narrow, orstop, present every recordedWORK_FAILbacklog to the human/design decision for explicit repair, deferral, removal, narrowing, or stop; none of those routes is autonomous. Material design changes repeat the applicable QbD decision.
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 · 77 lines · 25 tokens per session scan A 1853b48bbea0
omp-flow-execute is a skill published in the GitHub repository Andyduck-ops/omp-flow (5 stars, last pushed 7d ago), licensed MIT. It adds 25 tokens to every session and 1,029 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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