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-debugnpx skills add Andyduck-ops/omp-flow --skill omp-flow-debuggit 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 | $0.00028 | $0.00383 |
| Opus 5 | $0.00014 | $0.00192 |
| Sonnet 5 | $0.00006 | $0.00077 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
omp-flow-debug 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
OMP-Flow Debug
Procedure
- Start from the assigned Bundle root, relevant entry Concept, output boundary, actor identity, operation receipt, and predecessor receipt when present. Preserve the exact error, arguments, raw log path, session identity, Harness version, and runtime operation observation.
- Read the entry Concept and follow only links useful to the failure. Do not reconstruct semantic input or infer task meaning from runtime JSON.
- Reproduce at the narrowest boundary that still fails.
- Classify the owner: Harness native task/model schema; Adapter assignment seam; Python mechanical validation; broken Concept/path/receipt binding; or product/test environment.
- Form falsifiable hypotheses and run the smallest discriminating experiment.
- Compare successful and failed calls structurally before trusting an error label. A gateway
400may describe the final request, not the root cause. - Repair only the assigned code/output boundary and write the promised linked diagnostic or implementation handoff Concept.
- Re-run the original operation without a fallback path and report exact commands/results, actor ID, receipt, output, and remaining uncertainty.
Failure Contract
If blocked, report facts, ruled-out hypotheses, remaining hypothesis, missing evidence, and the next discriminating action. Do not convert failure into partial success.
Red Flags
- No broad
catchthat continues with empty input. - No automatic global active-task or legacy-store fallback.
- No duplicate runtime dependency to mask a missing host export.
- No warning suppression or fabricated PASS.
- Do not retry an unchanged deterministic failure.
- Do not edit
.omp-flow/.runtime/directly or turn Concept prose into machine state.
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 · 38 lines · 28 tokens per session scan A 90341dc20355
omp-flow-debug is a skill published in the GitHub repository Andyduck-ops/omp-flow (5 stars, last pushed 6d ago), licensed MIT. It adds 28 tokens to every session and 383 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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