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github-issue-opsIndustrialize GitHub issue campaigns

From code-search results to EPIC issues and per-repo sub-issues in seconds.

Use cases

Tech-debt campaign

Search for deprecated API usages → issue create → assign to teams → issue dispatch

Security patch rollout

Search for vulnerable dependency → issue create → update weekly with issue refreshissue dispatch

Compliance enforcement

Search for missing licence headers → issue create → track progress via EPIC checklist

Framework migration

Search for legacy import patterns → issue createissue dispatch per team

Works with any tool that produces Markdown or JSON: github-code-search, custom scripts, or AI-generated reports.

Why github-issue-ops in the agentic AI age?

AI coding agents generate code at unprecedented speed — and with it, new technical debt, security gaps, and compliance issues land across dozens of repositories simultaneously.
Traditional issue triage doesn't scale: an agent can introduce a problem in 50 repos in the time it takes a human to open a single ticket.

github-issue-ops closes this loop. It turns a structured search result — produced by a human, a CI check, or an AI agent itself — into a traceable GitHub issue campaign:

SystematicEvery affected repository gets its own sub-issue — no repo is missed.
IdempotentRun the same command twice — the campaign is not duplicated.
RefreshableAs the agent fixes repos, issue refresh updates the EPIC in real time.
AuditableMetadata is embedded in the issue body; the full replay command is always one click away.
In an agentic world, github-issue-ops is the missing link between "AI found a problem at scale" and "every team knows about it, owns it, and can close it".

Used in production?

github-issue-ops is developed and used internally at fulll to drive organisation-wide refactoring and compliance campaigns across hundreds of repositories.

Using it at your organisation? Share your experience in GitHub Discussions.

Released under the MIT License.