What problem does it solve? Product owners and maintainers of openai/codex need a fast way to see which bug reports and enhancement requests are gaining user attention, without manually scanning GitHub issues across many feature-area labels. ## Core Features & Use Cases - Label-scoped issue collection: Runs a Python collector via the GitHub CLI to gather bug and enhancement issues for specific owner labels (e.g., tui, exec, app) or across all labels. - Attention scoring: Counts unique human interactions (new issues, comments, reactions) within a configurable window and marks elevated items with fire markers scaled to the window length. - Headline-first reporting: Produces a summary-first digest with optional details tables, inline numbered issue references, and a compact source line citing script version, git head, and time window. - Use Case: A TUI owner asks for the digest of labels tui and exec over the past week and receives a headline naming the top user-surfaced issues with links, plus an optional details table. ## Quick Start Use $codex-issue-digest to run the Codex issue digest for labels tui and exec over the previous 24 hours.
