agent-doc-discipline
Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and…
Evaluate finished work for defects, risk, and simplification before it ships
Claude Code
$ npx -y skills add Yeachan-Heo/oh-my-claudecode --skill review --agent claude-code
Codex
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a codex -y
Cursor
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a cursor -y
Gemini CLI
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a gemini-cli -y
GitHub Copilot
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a github-copilot -y
OpenCode
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a opencode -y
Windsurf
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill review -a windsurf -y
name: omc-review description: Evaluate finished work for defects, risk, and simplification before it ships
Use this skill to evaluate work that already exists. Review never authors the change it is judging.
This is the canonical review workflow. `ai-slop-cleaner` is an opt-in lane within it.
Find what is actually wrong, ranked by severity, with enough detail to act on.
1. Establish what changed and what it was meant to do. 2. Read the change against that intent. 3. Check correctness first, then risk, then simplification. 4. Verify each candidate finding before reporting it. 5. Report findings most-severe first.
A substantial diff is reviewed as two parallel sub-agent passes, reported separately — never merged or cross-ranked, because a change can pass one axis and fail the other (standards-conforming but wrong behavior; faithful but convention-breaking):
Keep each sub-agent brief under ~400 words and pointed at one axis. Aggregate without picking a single winner across axes — that reranking is what the separation exists to prevent; state each axis's verdict on its own. A small diff stays one pass.
security, destructive operations) stay separate and fail closed.
Before finalizing the review, check the existing merged OMC `qualityGates["omc-review"]` entries (project stage entries replace the user list; see `docs/quality-gates-configuration.md`). If there are no entries, do not call `omc quality-gates list`, spawn gate tasks, or add a Quality Gates section or gate records to the review output. If there is at least one entry, call `omc quality-gates list --stage omc-review --json` and show every validation error. For each available gate, spawn one independent Claude Code `Task` that loads the named skill from `resolvedPath`, reviews the same changes, and returns `VERDICT: PASS` or `VERDICT: BLOCK` plus findings. Use the configured model override when present; do not pass another reviewer's output to the gate. Reuse the same gate lane if the change is revised and reviewed again.
When gates are configured, record `{ gate, mode, verdict }` for each gate in a Quality Gates section of the review output. Unresolved skills are `gate_unavailable` with a visible warning, never PASS; they do not fail the review stage. A blocking `BLOCK` makes the overall result `REQUEST CHANGES`; advisory results are informational and never block.
For Codex users: Check out oh-my-codex — the same orchestration experience for OpenAI Codex CLI. Liked OmC but found it a bit overkill? Try gajae-code.
Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and…
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