Omh AI Slop Cleaner

Ai Slop Cleaner

This is a Hermes-native ai-slop-cleaner workflow skill.

Why This Exists

ai-slop-cleaner exists to keep maintenance work explicit, evidence-backed, and inside the Hermes/executor boundary instead of relying on ad hoc chat narration.

Do Not Use When

• The goal is new or changed behavior rather than removing existing code; a plain refactor, feature, or fix request belongs to ultrawork.
• The cleanup would change architecture or module boundaries and needs its execution shaped into phases first; use refactor-plan, or ralplan when the direction itself is still contested.
• The user wants existing code judged rather than changed; use code-review for a bug-first review and failure-signal-audit for swallowed failures.

Examples

Good example:

• Prompt: $ai-slop-cleaner remove duplicated router branches and lock behavior with regression tests before refactoring.
• Expected behavior: Plan cleanup, preserve behavior, delete or simplify code, and prove it with targeted tests.
• Why: The request is maintenance cleanup with regression risk.

Bad example:

• Prompt: ai-slop-cleaner: treat casual chat or unaccepted work as if this workflow already produced verified results.
• Expected behavior: Ask a clarification question or route to a narrower workflow instead of forcing ai-slop-cleaner.
• Why: The request lacks the required inputs or would overclaim work that Hermes did not observe.

Completion Checklist

• The selected coding or runtime owner is named before any implementation claim.
• Prepared handoff, dispatch, execution, verification, review, CI, and merge states are separated.
• The final status cites observed runtime evidence or keeps the work prepared_not_observed.
• When Hermes is the selected coding owner, use hermes_coding_harness/v1 to keep builder, verifier, reviewer, docs, and PR lanes separate.
• Report the current harness stage, owner, next action, and missing evidence without claiming PR creation, review, CI, merge-readiness, or merge until matching runtime observations exist.

Recovery Notes

• If the selected executor is unavailable, ask for Codex, Claude Code, Hermes, or another runtime before retrying.
• If dispatch or result evidence is missing, keep the handoff prepared_not_observed and expose the next observable action.

Workflow Lane

• Current lane: Coding handoff (idea-to-deploy, llm-app-dev, cto-loop, deploy-and-monitor, code-review, build-failure-triage, verification-gate, security-safety-review, +28 more) - coding owners, handoffs, review, CI, and merge evidence.
• If intent belongs to another lane, hand back to oh-my-hermes or name the adjacent workflow.
• Shared product, routing, compatibility, and evidence rules: omh-routing/references/skill-common-rail.md.

Use When

Use when the goal is removing existing low-quality, duplicated, or AI-generated code and the observable behavior must not change; lock behavior with tests before and after the edits.

Strong routing signals: `ai-slop-cleaner`, `$ai-slop-cleaner`, `cleanup`, `deslop`, `refactor`, `risky`, `behavior-preserving refactor`, `risk analysis`, `refactor workflow`, `legacy refactor`, `리팩터링`, `리팩토링`, `위험 분석`, `변경 범위 제한`, `회귀 테스트`

Catalog Metadata

Category: maintenance Phase: cleanup Hermes role: handoff-guide Quality tier: regression-gated Reasoning demand: heavy

Quality bar:

• Lock current behavior with regression checks before non-trivial cleanup.
• Classify before deleting: every finding names one category from the slop taxonomy - duplication, dead code, needless abstraction, boundary violation, missing tests, or templated defaults - so the pass order below can own it.
• Run single-smell passes in fixed order, re-verifying between passes and never bundling categories: dead-code deletion, then duplicate removal, then naming and error handling, then test reinforcement; the full contract is omh-ai-slop-cleaner/references/cleanup-passes.md.
• When the user names no target smell, run detection first and hand back the inventory: prepared linter and dead-code commands are named per stack in the reference and stay prepared_not_observed until run.
• When the cleanup target is written English rather than code, load omh-ai-slop-cleaner/references/prose-lexicon.md for the word tiers, the pattern severities, and the context profile that decides which rules apply.
• Prefer deletion, reuse, and boundary repair over new abstractions.
• Rerun verification after cleanup before claiming behavior is preserved, and close with the four-part report: changed files, simplifications, behavior lock, remaining risks.

Handoff policy:

Use Hermes to define cleanup scope and regression checks; route behavior-preserving edits to the selected coding runtime once tests are clear.

Executor readiness:

• When accepted work mutates code, check executor_readiness/v1 for the selected Codex, Claude Code, Hermes, or oh-my runtime path before first dispatch.
• If readiness is missing or blocked, ask the user to choose another coding agent, configure PATH, continue in Hermes, or keep a prompt/runtime handoff; retry only after that state changes.
• A readiness probe is not dispatch, implementation, verification, review, CI, merge-readiness, or merge evidence.

Delegation transparency:

• When delegating, show the composed delegate prompt in a fenced code block in the status message; truncate a long prompt to a bounded preview ending with ... [truncated, N chars total] — the user must see WHAT was asked, not just that something was.
• Name every delegated or parallel lane's model and, when the host exposes it, its reasoning effort inline as (model effort) in status and briefing lines — including runtime-native subagents; when no effort is exposed, show the model alone as (model) rather than writing a placeholder like unknown beside a known model, and never emit empty parentheses. Carry token and elapsed figures the same way in these narration lines: report observed figures and omit unobserved ones — when the user asks for a figure directly, say it was not observed instead of omitting it; a rendered status-board column keeps its own unknown cell.
• Capture a resumable session or thread id at dispatch and report it in the status message: for non-interactive Claude Code pass --output-format json and read session_id from the result (resume with claude -p --resume <session-id>); for Codex pass --json and read thread_id (resume with codex exec resume <thread-id>, repeating --skip-git-repo-check outside a git repo). Never leave a delegate run with no recorded way to resume or steer it — a plain-text one-shot that hides its session id strands the work when the run stalls or times out.
• Before dispatch, grant the executor session every permission the task will need — file write/edit, command/test execution, and the working directory — on the dispatch command itself, not through settings-file guesses: for non-interactive Claude Code pass --permission-mode acceptEdits or an explicit --allowedTools list (--dangerously-skip-permissions only inside an isolated worktree or sandbox), and the equivalent sandbox/approval flags for other CLIs. acceptEdits: true is not a settings key and ~/.claude/settings.local.json is not a file Claude Code reads — user scope is ~/.claude/settings.json and project scope is the dispatch cwd's .claude/settings.local.json with rules under permissions.allow. Prove the grant with a bounded scratch-edit probe run before the real dispatch: a permission denial in a non-interactive run recurs identically on retry, so never redispatch until a changed grant is proven, and surface an ungrantable permission as a blocker before dispatch, not after minutes of silence.