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 skills add strikersam/autonomous-ai-agency --skill workflow-enginegit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/strikersam/autonomous-ai-agency/workflow-engine)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/workflow-engine"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/workflow-engine/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/workflow-engine"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/workflow-engine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00019 | $0.00241 |
| Opus 5 | $0.00010 | $0.00120 |
| Sonnet 5 | $0.00004 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
workflow-engine 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 6d 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
Skill: SuperClaude Workflow Engine
Purpose
DAG-based workflow execution engine (agents/workflow_engine.py) with topological ordering,
cycle detection, and dependency resolution.
Usage
from agents.workflow_engine import WorkflowEngine, Workflow, Task
engine = WorkflowEngine()
wf = Workflow(workflow_id="deploy", name="Deploy Pipeline")
wf.add_task(Task(task_id="build", name="Build", action=lambda: "built"))
wf.add_task(Task(task_id="test", name="Test", action=lambda: "tested", depends_on=["build"]))
engine.register(wf)
results = engine.execute("deploy")
Key Classes
- Task — single DAG node with action, dependencies, status, retries
- Workflow — named collection of tasks, DAG validation, ready-task detection
- WorkflowEngine — registry, topological execution
Testing
python -m pytest tests/test_workflow_engine.py -v
Related Issues
- Issue #235: SuperClaude Workflow Engine
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.
- 6d ago First seen · 37 lines · 19 tokens per session scan A ffe61122ae91
workflow-engine is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed yesterday), licensed MIT. It adds 19 tokens to every session and 241 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 2026-09-03.
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