AI Agent Workflow Collection

Add or rewrite code comments with calibrated granularity so they explain intent, constraints, data meaning, contracts, and control-flow decisions instead of translating syntax. Use when Codex is asked to document existing code, improve low-value comments, add structured comments to functions, interfaces, classes, types, fields, exported constants, configuration objects, state transitions, or complex internal logic while preserving the repository's existing comment language and style.

Perform a scoped, coverage-led review of a working tree, staged diff, commit range, branch diff, PR, or suspicious implementation to find hack-like implementation risks. Use when Codex must audit brittle shortcuts such as impossible-state fallbacks, masked root causes, duplicate abstractions, hardcoded special cases, boundary bypasses, hidden temporal coupling, write-then-fix-up flows, or other ownership problems, and must write a Markdown report that enumerates all distinct hack-risk findings discovered within the reviewed scope plus coverage gaps and intentional exceptions.

Consume a coverage-led hack-review Markdown report, PR feedback derived from one, or a request to address Block, Discuss, Watch, Intentional Exceptions, Complete Hack-Risk Index, Ownership Coverage Ledger, Not covered, or coverage-gap items. Use when Codex must verify whether each reported shortcut, ownership problem, intentional exception, and uncovered implementation boundary still applies before changing code, then fix, disprove, narrow, confirm, or carry forward every item with evidence while leaving Git staging untouched unless the user explicitly asks for staging, committing, or PR publication in the current request.

Consume a coverage-led regression-review Markdown report or related PR feedback and turn it into evidence-backed next actions. Use when Codex is given Block, Discuss, Watch, Intentional Changes, Complete Findings Index, Coverage Ledger, Not covered, or coverage-gap items from a regression-review report and must verify whether each user-visible finding still applies, fix proven regressions, disprove or challenge stale findings, confirm intentional product changes, close coverage gaps, and report a disposition for every item before changing or claiming completion while leaving Git staging untouched unless the user explicitly asks for staging, committing, or PR publication in the current request.

Perform a scoped, coverage-led review of working tree, staged, commit-range, branch, or PR changes to find user-visible behavioral regressions. Use when Codex must audit code changes for broken or degraded user journeys, changed defaults, loading/error/permission/session behavior, stale data, ordering, retries, duplicate/destructive actions, exported output, emails, CLI output, or other visible behavior, and must write a Markdown report that enumerates all distinct findings discovered within the reviewed scope plus coverage gaps and intentional visible changes.

Split a large or mixed Git working tree into multiple focused local commits. Use when changes span unrelated concerns, combine refactors with behavior changes, mix generated files with source edits, or contain separable hunks in the same file, and Codex needs to stage one logical batch at a time, invoke $git-commit to draft the staged commit message, present the staged batch for user confirmation, run git commit only after the user explicitly approves that batch, and repeat without pushing.