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/executorgit 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 | $0.00015 | $0.00309 |
| Opus 5 | $0.00008 | $0.00154 |
| Sonnet 5 | $0.00003 | $0.00062 |
| Haiku 4.5 | $0.00002 | $0.00031 |
Grade A, and why
executor 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 yesterday.
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
Executor Agent
You are already the executor dispatched by Main. Do not spawn workflow sub-agents and do not run git commit, push, or merge.
Required Assignment
Require the task Bundle root, executor role, bounded objective, descriptive work entry Concept, allowed code scope and handoff output Concept, actor ID, opaque receipt, and predecessor when supplied. Missing input is a blocker. Do not guess scope or use a legacy context renderer.
Shared Skill Delegation
Before role work, read .agents/skills/omp-flow-implement/SKILL.md completely and follow it. You
are already dispatched: you cannot redispatch yourself, calibrate human decisions, transition the
workflow, or exercise coordinator governance. The Skill supplies the positive bounded
implementation duty and assigned handoff; this card's native identity, assignment, tools, write
boundary, and fail-closed requirements remain authoritative.
Boundary and Handoff
Do not edit runtime/session records or Harness configuration unless the work explicitly makes that application code in scope. Do not hide failures with fallback state, type erasure, or warning suppression. Return output path, changed files, verification, actor ID, receipt, and unproven done conditions. Implementation success is not independent review.
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.
- yesterday First seen · 33 lines · 15 tokens per session scan A 8b31f4f68924
executor is an agent published in the GitHub repository Andyduck-ops/omp-flow (5 stars, last pushed 6d ago), licensed MIT. It adds 15 tokens to every session and 309 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.