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 vasilyu1983/AI-Agents-public --skill software-workflow-automationgit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/software-workflow-automation)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/software-workflow-automation"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-workflow-automation/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/vasilyu1983/ai-agents-public/software-workflow-automation"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/software-workflow-automation.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 | $0.00038 | $0.03824 |
| Opus 5 | $0.00019 | $0.01912 |
| Sonnet 5 | $0.00008 | $0.00765 |
| Haiku 4.5 | $0.00004 | $0.00382 |
Grade A, and why
software-workflow-automation 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 9d 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Automation
Use this skill to choose and design software workflow automation when the system needs triggers, integrations, routing, approvals, or AI-assisted steps across tools and services.
This skill covers:
- platform choice between n8n, Langflow, Huginn, Temporal, Trigger.dev, and custom code
- event-driven workflow design for internal tools and product operations
- side-effect control, retries, approvals, and observability
- AI-assisted workflow steps without turning every flow into a full agent system
- handoff rules for when visual automation should become code
Quick Reference
| Need | Default path | Notes |
|---|---|---|
| Broad integration workflow with many SaaS connectors | n8n | Strong default for business and product operations with many external systems. Fair-code Sustainable Use License — free for internal business use; check terms before reselling hosted access. |
| Visual AI or LLM pipeline prototyping | Langflow | Best fit when the workflow is model-centric and still evolving quickly. Open source, IBM-stewarded since the DataStax acquisition; the DataStax-hosted managed product was retired in early 2026 — self-host or re-check current managed options. |
| Self-hosted event watchers and automation agents | Huginn | Good fit for monitoring, alerts, and privacy-first self-hosted automations; upstream project has low recent activity — evaluate community forks before committing |
| Long-running, retried, or replay-sensitive business workflows | Temporal or Trigger.dev v4 | Use when durable execution, idempotency, and code review matter more than visual editing speed. Trigger.dev v3 was fully shut down 2026-07-01 — v4 is the only supported line. |
| Complex state, strong testing, or strict SLOs | Custom code | Move out of no-code/low-code once the workflow becomes core software |
| Tool protocol or reusable tool surface | ../agents-mcp/SKILL.md |
MCP is the integration contract layer, not the workflow designer itself |
| Platform state, version traps, and migration notes (verify before advising) | references/platform-state.md | Temporal (Nexus GA), Trigger.dev v4, n8n 2.x, Inngest, Hatchet 1.0, LangGraph vs Langflow |
| Durable execution deep-dive: Temporal, Trigger.dev v4, n8n 2.x, LangGraph/Langflow | references/durable-execution.md | breaking changes and production traps |
| Replay DLQ messages from a JSON file | scripts/replay_dlq.py | generic scaffold; adapt TARGET_COMMAND_TEMPLATE |
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 344 B
- data/sources.json 4.5 KB
- evals/evals.json 7.9 KB
- learnings.consolidated.md 604 B
- learnings.md 1.3 KB
- references/automation-governance.md 3.8 KB
- references/durable-execution.md 11 KB
- references/platform-selection.md 1.4 KB
- references/platform-state.md 17 KB
- scripts/check_workflow_idempotency.py 13 KB runs code
- scripts/replay_dlq.py 6.3 KB runs code
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.
- 9d ago First seen · 219 lines · 38 tokens per session scan A c3b7d12f71e1
software-workflow-automation is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 38 tokens to every session and 3,824 once invoked, about $0.0002 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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