agentic-ops"Audit AI credit spend, surface waste, and optimize agentic workflows with confidence!"
agentic-ops is a focused bundle of GitHub Agentic Workflows for teams scaling agentic automation and wanting better visibility into usage, trends, and optimization opportunities. Instead of guessing which workflows are driving the highest AI credit spend or where waste is hiding, this package gives you an audit trail, historical reporting, and conservative recommendations you can review before making changes.
It is built for platform engineers, developer productivity teams, and repository maintainers who are scaling agentic workflows and need a practical way to keep them efficient. The bundle helps solve a common problem with AI automation: token usage grows quickly, but the signals for where to improve are scattered across workflow runs and logs. With agentic-ops, you get repeatable workflows that make usage measurable, optimization opportunities actionable, and efficiency work easier to operationalize.
Prerequisites:
gh aw)gh auth login) in the repository where you want to install the workflowsInstall the package with gh aw add:
gh aw add githubnext/agentic-ops
# Then compile the installed workflows in your repository
gh aw compile
This repository publishes a single package at the repository root. You do not need to target a nested package path.
Required configuration after installation:
GITHUB_TOKEN.After installation, you can use the included workflows to:
Included workflows:
| Workflow | What it does |
|---|---|
Daily Agentic Workflow AIC Usage Audit | Collects recent agentic workflow usage and creates a daily AIC spend snapshot. |
Agentic Workflow AIC Usage Optimizer | Analyzes high-AIC workflows and proposes conservative efficiency changes, including inline sub-agent opportunities when they are a strong fit. |
MIT
agentic-ops"Audit AI credit spend, surface waste, and optimize agentic workflows with confidence!"
agentic-ops is a focused bundle of GitHub Agentic Workflows for teams scaling agentic automation and wanting better visibility into usage, trends, and optimization opportunities. Instead of guessing which workflows are driving the highest AI credit spend or where waste is hiding, this package gives you an audit trail, historical reporting, and conservative recommendations you can review before making changes.
It is built for platform engineers, developer productivity teams, and repository maintainers who are scaling agentic workflows and need a practical way to keep them efficient. The bundle helps solve a common problem with AI automation: token usage grows quickly, but the signals for where to improve are scattered across workflow runs and logs. With agentic-ops, you get repeatable workflows that make usage measurable, optimization opportunities actionable, and efficiency work easier to operationalize.
Prerequisites:
gh aw)gh auth login) in the repository where you want to install the workflowsInstall the package with gh aw add:
gh aw add githubnext/agentic-ops
# Then compile the installed workflows in your repository
gh aw compile
This repository publishes a single package at the repository root. You do not need to target a nested package path.
Required configuration after installation:
GITHUB_TOKEN.After installation, you can use the included workflows to:
Included workflows:
| Workflow | What it does |
|---|---|
Daily Agentic Workflow AIC Usage Audit | Collects recent agentic workflow usage and creates a daily AIC spend snapshot. |
Agentic Workflow AIC Usage Optimizer | Analyzes high-AIC workflows and proposes conservative efficiency changes, including inline sub-agent opportunities when they are a strong fit. |
MIT