Agent skill

Asw Remove AI Slops

by wjgoarxiv in wjgoarxiv/antigravity-swarm

Remove AI-looking code smells from branch changes or explicit files.

MITAuto-check passedTesting & QA

Install Asw Remove AI Slops

skills CLI
$ npx skills add wjgoarxiv/antigravity-swarm --skill asw-remove-ai-slops -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wjgoarxiv/antigravity-swarm asw-remove-ai-slops --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wjgoarxiv/antigravity-swarm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/antigravity-swarm/skills/asw-remove-ai-slops .claude/skills/asw-remove-ai-slops && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
asw-remove-ai-slops
GitHub stars
166
Token cost
~2.7k tokens
SKILL.md length
1,294 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Remove AI-looking code smells from branch changes or explicit files.

  • Works in 12 steps: Obvious Comments → Over-Defensive Code → Excessive Complexity → …
  • Tasks that involve Quality gates
  • SKILL.md covers Inputs, What this skill does, Categories and Quality Gates, plus 4 more sections
  • Calls git

What it does

Asw Remove AI Slops is an agent skill from wjgoarxiv/antigravity-swarm. Remove AI-looking code smells from branch changes or explicit files. Lock behavior with regression tests first, run categorized cleanup in bounded Antigravity lanes, then verify with quality gates.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering Quality gates and Refactoring. The repository describes itself as: ::A team of AI agents to code for you.::. The licence is MIT.

When your agent uses it

  • Tasks that involve Quality gates
  • Tasks that involve Refactoring

Example prompts

  • “/asw-remove-ai-slops”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Obvious Comments
  2. Over-Defensive Code
  3. Excessive Complexity
  4. Needless Abstraction
  5. Boundary Violations
  6. Dead Code
  7. Duplication
  8. Performance Equivalences
  9. Missing Tests
  10. Oversized Modules
  11. Plan
  12. Determine scope

What it can do on your machine

Read from SKILL.md and the folder at commit a949cb8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Asw Remove AI Slops loads about 2.7k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 1,294 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wjgoarxiv/antigravity-swarm at commit a949cb8, republished under its MIT licence (© wjgoarxiv). 1,294 words, ~2,706 tokens.

Download SKILL.mdSave it as .claude/skills/asw-remove-ai-slops/SKILL.md (or your agent's skills folder).
name
asw-remove-ai-slops
description
Remove AI-looking code smells from branch changes or explicit files. Lock behavior with regression tests first, run categorized cleanup in bounded Antigravity lanes, then verify with quality gates.

Antigravity Swarm Remove AI Slops

Use this skill when the user asks to remove slop, clean generated-looking code, deslop a branch, remove noisy comments, simplify over-defensive logic, or tidy recent AI-assisted changes.

The invariant: behavior is locked before cleanup. A checklist is not safety. A passing characterization or regression check is the safety mechanism.

Inputs

  • Default scope: changed files in the current branch compared with the merge base of main.
  • Optional scope: an explicit file list from the user or from an ASW plan.
  • Accepted file types: source, tests, docs, installer scripts, hook scripts, and configuration files owned by the current change.
  • Excluded file types: deleted files, binaries, vendored directories, generated output, lockfiles unless the lockfile is the requested surface.

What this skill does

This skill cleans a bounded set of files while preserving behavior.

It does four things:

  1. Determines scope.
  2. Locks current behavior with tests or characterization checks.
  3. Runs categorized cleanup in safe order.
  4. Verifies with quality gates and an ASW review.

It does not:

  • change public APIs unless the user explicitly asked,
  • remove validation at external boundaries,
  • rewrite architecture for taste,
  • optimize code when behavior equivalence is not obvious,
  • claim completion from green tests alone.

Categories

1. Obvious Comments

Remove:

  • comments that restate the next line,
  • trivial docstrings on self-explanatory functions,
  • section banners,
  • commented-out code,
  • vague TODOs without owner or issue,
  • notes that expose internal process instead of product behavior.

Keep:

  • comments explaining why,
  • issue links,
  • algorithm notes,
  • regex explanations,
  • boundary or compatibility constraints,
  • BDD markers in tests.
2. Over-Defensive Code

Remove or simplify:

  • null checks for guaranteed values,
  • default values for required parameters,
  • broad catches around code that cannot throw,
  • duplicated validation after a trusted parse step,
  • stale compatibility shims no longer documented or tested,
  • empty catches and log-only catches that swallow unknown failures.

Keep:

  • validation at user input, network, filesystem, subprocess, database, and external API boundaries,
  • nullable data handling,
  • top-level CLI or server boundary error handling with explicit reporting,
  • security checks.

When narrowing broad catches, handle known errors and rethrow unknown errors.

3. Excessive Complexity

Look for:

  • nesting deeper than three levels,
  • nested ternaries,
  • boolean expressions with four or more predicates,
  • long parameter lists,
  • functions doing several responsibilities,
  • type or variant discrimination through long conditional chains,
  • generic catch-all object shapes where a typed shape is known.

Preferred cleanup:

  • guard clauses,
  • named intermediate values,
  • small responsibility extraction,
  • exhaustive variant handling in the local language,
  • typed input parsing at the boundary.

Skip when:

  • the pattern is established and clearer in this codebase,
  • the path is performance-critical and intentionally shaped,
  • the simplification would require a behavior proof you do not have.
4. Needless Abstraction

Remove:

  • pass-through wrappers,
  • single-use helpers that hide simple code,
  • speculative interfaces,
  • factories that only call constructors,
  • indirection created only because future changes might happen.

Keep:

  • abstractions with multiple implementations,
  • test seams that reduce real coupling,
  • framework-required boundaries,
  • public extension points.
5. Boundary Violations

Flag and fix only when safe:

  • UI or command layer importing storage internals,
  • hook scripts owning installer policy,
  • package tests depending on private reference trees,
  • docs claiming behavior not covered by the package,
  • pure-named functions with hidden side effects.

When unsure, report the boundary issue and skip the edit.

6. Dead Code

Remove:

  • unused imports,
  • unused private helpers,
  • unreachable branches,
  • stale feature flags,
  • debug output,
  • removed-code comments,
  • orphaned exports not referenced by docs, tests, package manifests, or dynamic lookup.

Keep:

  • dynamic dispatch targets,
  • plugin manifest entries,
  • public exports,
  • intentional rollback flags with evidence.
7. Duplication

Remove:

  • copy-pasted branches with trivial differences,
  • repeated literal sequences,
  • redundant helpers doing the same thing,
  • duplicated package or hook path logic.

Keep:

  • similar code with different intent,
  • local duplication that is clearer than premature sharing.
8. Performance Equivalences

Apply only when behavior equivalence is obvious:

  • list scan to set lookup,
  • repeated computation in a loop hoisted outside,
  • eager collection to lazy iteration,
  • string concatenation in loop to join,
  • repeated API or database calls batched when result ordering and errors stay the same,
  • redundant clones or deep copies removed,
  • repeated length checks cached when the collection cannot mutate.

Do not:

  • alter algorithms with subtle correctness conditions,
  • micro-optimize without a benchmark,
  • change ordering, exception timing, or side effects.
9. Missing Tests

If changed behavior is uncovered, add the narrowest regression test before cleanup. The fix is not to remove code; the fix is to lock behavior.

Tests should pin observable outputs, public errors, package contents, generated files, or CLI text rather than private implementation details.

Show full SKILL.md (554 more words)Show less
10. Oversized Modules

Any source file over 250 pure lines is a design smell unless it is a clearly self-contained script.

Measure pure lines by excluding blanks and comments.

When oversized files are in scope:

  1. Identify responsibilities.
  2. Name target files by concept, never utils, helpers, common, or numbered chunks.
  3. Preserve public imports and package paths.
  4. Extract one responsibility at a time.
  5. Re-run tests and diagnostics after each extraction.
  6. Report any intentionally unsplit file with evidence.

Do not split generated output. Do not split by token count.

Quality Gates

Run every applicable gate. Mark genuinely absent gates as N/A with a reason.

GatePass condition
Behavior lockrelevant tests or characterization checks green before cleanup
Regression testsall relevant tests green after cleanup
Full suiteproject test runner green, or pre-existing failures named
Lint/formatzero new errors
Typecheck/diagnosticszero new diagnostics in changed files
Package surfacenpm or plugin package excludes private/runtime material
Manual QAreal CLI, hook, installer, browser, HTTP, or desktop surface exercised when user-visible behavior changed
ReviewASW reviewer has no blockers

Process

Phase 0: Plan

Create a short cleanup plan before editing:

text
Scope:
- file

Behavior lock:
- test or characterization command

Cleanup order:
- comments -> dead code -> defensive -> duplication -> complexity -> abstraction/boundary -> performance -> oversized modules

Risk:
- low | medium | high
Phase 1: Determine scope

If the user passed paths, use those paths.

Otherwise inspect the branch diff:

bash
git diff "$(git merge-base main HEAD)"..HEAD --name-only

Filter:

  • deleted files,
  • binary files,
  • generated output,
  • vendored directories,
  • lockfiles unless they are the requested surface.

List final scope before cleanup.

Phase 2: Lock behavior

For each in-scope source file:

  1. Identify observable behavior.
  2. Find existing tests.
  3. Add a characterization test if coverage is weak.
  4. Run the relevant test and confirm it is green before editing.

If no green baseline can be established, stop and report. Do not clean uncovered behavior.

Phase 3: Cleanup plan

For each file, list categories and order:

text
File: path
Categories: comments, dead code, defensive
Order: comments -> dead code -> defensive
Risk: low
Behavior lock: command/test id
Phase 4: Parallel cleanup

For multiple independent files, use Antigravity subagents in batches of up to five.

Per-file lane message should include:

  • exact file,
  • categories to evaluate,
  • behavior lock evidence,
  • cleanup order,
  • hard constraints,
  • report format.

Hard constraints for each lane:

  • preserve behavior,
  • do not change public API signatures,
  • do not remove type hints,
  • do not introduce dependencies,
  • skip uncertain performance changes,
  • keep diff minimal.

If a lane fails, collect successful lanes, retry the failed file once, then escalate.

Phase 5: Verify

Run the quality gates. Then walk the critical review checklist:

Safety:

  • no functional logic accidentally removed,
  • all boundary error handling preserved,
  • types and imports intact,
  • public APIs stable.

Behavior:

  • return values unchanged,
  • side effects unchanged,
  • exception behavior unchanged,
  • edge cases preserved.

Quality:

  • removed code was genuine slop,
  • remaining code follows project conventions,
  • no orphaned references,
  • no subtle performance changes,
  • no speculative abstraction added.
Phase 6: Fix issues

If a gate fails:

  1. Identify the exact hunk.
  2. Explain why it failed.
  3. Revert only that hunk.
  4. Apply a safer edit if genuine slop remains.
  5. Re-run the failing gate.
  6. Stop after repeated failure and report the file, attempts, and hypothesis.

Output Format

text
AI SLOP REMOVAL REPORT
======================

Scope:
Files:

Behavior Lock:
- Existing coverage:
- Tests added:
- Baseline status:

Cleanup Plan:
- path: categories in order

Per-File Results:
path
- Category: change summary
- Skipped: preserved for safety

Quality Gates:
- Behavior lock:
- Regression tests:
- Full suite:
- Lint:
- Typecheck:
- Package surface:
- Manual QA:
- Review:

Critical Review:
- Safety:
- Behavior:
- Quality:

Issues Found & Fixed:
- None | details

Remaining Risks / Deferred:
- None | details

Final Status: CLEAN | ISSUES FIXED | REQUIRES ATTENTION

Anti-Patterns

  • Skipping behavior lock.
  • Bundling unrelated refactors.
  • Calling a performance change safe without obvious equivalence.
  • Silently skipping gates.
  • Removing comments that explain why.
  • Touching files outside scope.
  • Deleting tests or weakening assertions.
  • Calling green tests completion without a real surface when users observe the behavior.

Final Rule

When in doubt, skip the cleanup and report the suspected slop. False negatives are better than broken behavior.

© wjgoarxiv, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/antigravity-swarm/skills/asw-remove-ai-slops of wjgoarxiv/antigravity-swarm.

Open the folder on GitHubat commit a949cb8

Compare with similar skills

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Sonarqube Analysishbmartin/graphviz2drawio275—~508Automated safety check: NotesGPL-3.0
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Categories

Questions about Asw Remove AI Slops

What does Asw Remove AI Slops do?

Remove AI-looking code smells from branch changes or explicit files. Asw Remove AI Slops is an agent skill from wjgoarxiv/antigravity-swarm. Remove AI-looking code smells from branch changes or explicit files.

When should I use Asw Remove AI Slops?

Asw Remove AI Slops fits situations like: tasks that involve Quality gates; tasks that involve Refactoring.

How do I install Asw Remove AI Slops in Claude Code?

Run `npx skills add wjgoarxiv/antigravity-swarm --skill asw-remove-ai-slops -a claude-code`. Or copy the skill folder (plugins/antigravity-swarm/skills/asw-remove-ai-slops in wjgoarxiv/antigravity-swarm) into .claude/skills/asw-remove-ai-slops in your project. Claude Code loads it when a task matches its description.

How do I install Asw Remove AI Slops in Codex?

Run `npx skills add wjgoarxiv/antigravity-swarm --skill asw-remove-ai-slops -a codex`. Or copy the skill folder (plugins/antigravity-swarm/skills/asw-remove-ai-slops in wjgoarxiv/antigravity-swarm) into .agents/skills/asw-remove-ai-slops in your project. Codex loads it when a task matches its description.

Can I use Asw Remove AI Slops in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wjgoarxiv/antigravity-swarm --skill asw-remove-ai-slops -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/asw-remove-ai-slops, .gemini/skills/asw-remove-ai-slops, .github/skills/asw-remove-ai-slops and .opencode/skills/asw-remove-ai-slops in your project.

What does Asw Remove AI Slops need to run?

Going by SKILL.md and its folder, Asw Remove AI Slops needs the command-line tools its instructions call (git).

Does Asw Remove AI Slops access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Asw Remove AI Slops safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Asw Remove AI Slops use?

Asw Remove AI Slops is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Asw Remove AI Slops use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Asw Remove AI Slops?

Skills that share tags, products or a category with Asw Remove AI Slops: Ccg Workflow (fengshao1227/ccg-workflow, 5.9k stars), Triage Sonarqube (netdata/netdata, 81k stars), Sonarqube Analysis (hbmartin/graphviz2drawio, 275 stars) and Code Solving (HoangTheQuyen/think-better, 122 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Asw Remove AI Slops?

wjgoarxiv (a GitHub user) maintains it in wjgoarxiv/antigravity-swarm, which has 166 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on June 19, 2026.

Source: wjgoarxiv/antigravity-swarm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.