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anti-ai-slop

After working on the code, ensure the branch contains only the minimal, idiomatic changes by removing AI-generated slop introduced on this branch.

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Price unconfirmed★ 41 GitHub starsRegistry updated · Oct 6, 2026agent-skill

Overview

After working on the code, ensure the branch contains only the minimal, idiomatic changes by removing AI-generated slop introduced on this branch.

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Intent

This skill reviews the diff against main and removes changes that are likely “AI slop”: unnecessary, non-idiomatic, or inconsistent additions that do not materially contribute to the intended feature/fix.

Guiding principle: keep the smallest change that accomplishes the goal, and match the local conventions of each touched file.

Scope and diff source

Operate only on changes introduced on this branch relative to main.

Determine the diff source in this order:

git diff --cached (if non-empty)
git diff (if non-empty)
git diff main..HEAD (fallback)
If main does not exist locally, use git diff master..HEAD.

Do not refactor unrelated code outside the displayed diff hunks.

Non-goals

Do not redesign architecture, rename APIs, or move code unless required by the feature/fix in the diff.
Do not remove meaningful domain comments that encode invariants, reasoning, constraints, or known pitfalls.
Do not remove validation at genuine trust boundaries (I/O, parsing, network, user input, third-party callbacks).
Do not change formatting rules; follow repository tooling and the file’s established style.

What counts as AI slop

A) Comment and documentation bloat

Remove comments/docstrings that merely narrate the code, restate names, or are inconsistent with the file’s comment density and tone.

Python (before):

def clamp(x: float, lo: float, hi: float) -> float:
    # Ensure x is not less than lo and not greater than hi
    if x < lo:
        return lo
    if x > hi:
        return hi
    return x

Python (after):

def clamp(x: float, lo: float, hi: float) -> float:
    if x < lo:
        return lo
    if x > hi:
        return hi
    return x

B) Unnecessary defensive checks inside trusted codepaths

Remove checks that are redundant because upstream validation/types/invariants already guarantee inputs.

Rust (before):

pub fn normalize_tag(tag: &str) -> String {
    if tag.is_empty() {
        return String::new();
    }
    tag.trim().to_ascii_lowercase()
}

If the rest of the codebase treats empty tags as impossible here (validated earlier), keep only the essential logic:

Rust (after):

pub fn normalize_tag(tag: &str) -> String {
    tag.trim().to_ascii_lowercase()
}

C) Try/catch / try blocks that add no value

Remove wrappers that only rethrow, add inconsistent logging, or hide errors without providing recovery.

C++ (before):

void SaveRow(Db& db, const Row& row) {
  try {
    db.Save(row);
  } catch (const std::exception& e) {
    std::cerr << "Error saving row: " << e.what() << std::endl;
    throw;
  }
}

If the repository does not use log-and-rethrow at this layer, prefer:

C++ (after):

void SaveRow(Db& db, const Row& row) {
  db.Save(row);
}

D) Single-use variables and one-off helpers that should be inlined

Prefer inlining when it improves clarity and matches surrounding style.

Python (before):

clean = s.strip().lower()
return clean

Python (after):

return s.strip().lower()

Rust (before):

let key = format!("{}:{}", user.id, user.region);
cache.insert(key, value);

If key is not reused and inlining remains readable:

Rust (after):

cache.insert(format!("{}:{}", user.id, user.region), value);

E) Redundant checks/casts duplicated at caller and callee

If a caller guarantees an invariant, remove repeated checks in the callee unless the subsystem consistently enforces invariants at every boundary.

Python (before):

def handle(req: Request) -> Response:
    user = parse_user(req)  # guarantees user.id is present
    return do_work(user)

def do_work(user: User) -> Response:
    assert user.id is not None
    return Response(user.id)

Python (after):

def do_work(user: User) -> Response:
    return Response(user.id)

F) Style drift and inconsistency with the file

Remove or rewrite changes that introduce new patterns inconsistent with the file or repository norms, such as:

Adding type annotations in a Python file that otherwise does not use them.
Introducing novel error-handling idioms in Rust (e.g., custom Result wrappers) where the module uses simple anyhow::Result (or vice versa).
Adding complex abstractions (factories/providers/managers) for small local logic.

G) Noisy logging and narration

Remove logs that restate the line of code, are inconsistent with the module’s logging level, or spam hot paths.

Rust (before):

log::info!("Starting normalization");
let out = normalize_tag(tag);
log::info!("Finished normalization");
out

Rust (after):

normalize_tag(tag)

(Keep logs that support production debugging when the module’s convention calls for them.)

H) Placeholder TODOs without a ticket/reference

Remove “TODO: handle edge cases” style notes that add no actionable guidance and are not aligned with repository practices.

I) Unicode hazards and emoji noise in code/comments

Remove suspicious or unnecessary Unicode in code and configs, including:

non-breaking spaces (U+00A0)
zero-width characters (U+200B, U+200D)
“smart quotes” (“ ” ‘ ’) in code/config
homoglyphs in identifiers
emojis in code comments/docs unless the repository explicitly uses them

Python (before):

# ✅ Done! 🚀
name = "abc"  # zero-width space

Python (after):

name = "abc"

(Do not “sanitize” legitimate localized/user-facing content unless it appears to be accidental.)

Trust boundaries: when defensive checks are appropriate

Defensive checks are generally appropriate at untrusted boundaries, such as:

request/CLI/env input handling
parsing and decoding (JSON, CSV, protobuf, HTML, etc.)
network/RPC boundaries
filesystem reads/writes of external data
third-party callbacks and plugin systems

Defensive checks are often slop within trusted internal pipelines, such as:

post-validated domain objects
post-auth/permission middleware
post-schema validation
internal-only transforms with strong invariants

When in doubt, follow existing patterns in the same module/subsystem.

Workflow checklist

Identify the diff source (cached, working tree, or main..HEAD).
For each changed hunk:
- Determine the intended behavior change.
- Remove additions that are not required to achieve it.
- Align with local style (naming, typing, error strategy, comment density).
Remove unused imports, dead code, and redundant helper layers introduced by the branch.
Keep changes minimal: avoid unrelated refactors.
Ensure changes still satisfy AGENTS.md (and other repo policies).
If repository tooling exists (formatters/linters/tests), avoid introducing new warnings.

Final report requirement

At the end, output only a 1–3 sentence summary describing what you changed. No bullet points. No emojis. No extended explanation.

Example acceptable summary:

Removed redundant input checks and log-and-rethrow blocks added in this branch, and inlined single-use helpers to match existing style. No functional behavior changes beyond the intended diff; all edits were confined to the branch’s modified hunks.

View source ↗

File metadata

name: anti-ai-slop
description: "After working on the code, ensure the branch contains only the minimal, idiomatic changes by removing AI-generated slop introduced on this branch."

View original text

---
name: anti-ai-slop
description: "After working on the code, ensure the branch contains only the minimal, idiomatic changes by removing AI-generated slop introduced on this branch."
---

## Intent

This skill reviews the **diff against main** and removes changes that are likely “AI slop”: unnecessary, non-idiomatic, or inconsistent additions that do not materially contribute to the intended feature/fix.

**Guiding principle:** keep the **smallest change that accomplishes the goal**, and match the **local conventions** of each touched file.

## Scope and diff source

Operate only on changes introduced on this branch relative to main.

Determine the diff source **in this order**:

1. `git diff --cached` (if non-empty)
2. `git diff` (if non-empty)
3. `git diff main..HEAD` (fallback)  
   If `main` does not exist locally, use `git diff master..HEAD`.

Do not refactor unrelated code outside the displayed diff hunks.

## Non-goals

- Do **not** redesign architecture, rename APIs, or move code unless required by the feature/fix in the diff.
- Do **not** remove meaningful domain comments that encode invariants, reasoning, constraints, or known pitfalls.
- Do **not** remove validation at genuine trust boundaries (I/O, parsing, network, user input, third-party callbacks).
- Do **not** change formatting rules; follow repository tooling and the file’s established style.

## What counts as AI slop

### A) Comment and documentation bloat

Remove comments/docstrings that merely narrate the code, restate names, or are inconsistent with the file’s comment density and tone.

**Python (before):**
```python
def clamp(x: float, lo: float, hi: float) -> float:
    # Ensure x is not less than lo and not greater than hi
    if x < lo:
        return lo
    if x > hi:
        return hi
    return x
```

**Python (after):**
```python
def clamp(x: float, lo: float, hi: float) -> float:
    if x < lo:
        return lo
    if x > hi:
        return hi
    return x
```

### B) Unnecessary defensive checks inside trusted codepaths

Remove checks that are redundant because upstream validation/types/invariants already guarantee inputs.

**Rust (before):**
```rust
pub fn normalize_tag(tag: &str) -> String {
    if tag.is_empty() {
        return String::new();
    }
    tag.trim().to_ascii_lowercase()
}
```

If the rest of the codebase treats empty tags as impossible here (validated earlier), keep only the essential logic:

**Rust (after):**
```rust
pub fn normalize_tag(tag: &str) -> String {
    tag.trim().to_ascii_lowercase()
}
```

### C) Try/catch / try blocks that add no value

Remove wrappers that only rethrow, add inconsistent logging, or hide errors without providing recovery.

**C++ (before):**
```cpp
void SaveRow(Db& db, const Row& row) {
  try {
    db.Save(row);
  } catch (const std::exception& e) {
    std::cerr << "Error saving row: " << e.what() << std::endl;
    throw;
  }
}
```

If the repository does not use log-and-rethrow at this layer, prefer:

**C++ (after):**
```cpp
void SaveRow(Db& db, const Row& row) {
  db.Save(row);
}
```

### D) Single-use variables and one-off helpers that should be inlined

Prefer inlining when it improves clarity and matches surrounding style.

**Python (before):**
```python
clean = s.strip().lower()
return clean
```

**Python (after):**
```python
return s.strip().lower()
```

**Rust (before):**
```rust
let key = format!("{}:{}", user.id, user.region);
cache.insert(key, value);
```

If `key` is not reused and inlining remains readable:

**Rust (after):**
```rust
cache.insert(format!("{}:{}", user.id, user.region), value);
```

### E) Redundant checks/casts duplicated at caller and callee

If a caller guarantees an invariant, remove repeated checks in the callee unless the subsystem consistently enforces invariants at every boundary.

**Python (before):**
```python
def handle(req: Request) -> Response:
    user = parse_user(req)  # guarantees user.id is present
    return do_work(user)

def do_work(user: User) -> Response:
    assert user.id is not None
    return Response(user.id)
```

**Python (after):**
```python
def do_work(user: User) -> Response:
    return Response(user.id)
```

### F) Style drift and inconsistency with the file

Remove or rewrite changes that introduce new patterns inconsistent with the file or repository norms, such as:

- Adding type annotations in a Python file that otherwise does not use them.
- Introducing novel error-handling idioms in Rust (e.g., custom `Result` wrappers) where the module uses simple `anyhow::Result` (or vice versa).
- Adding complex abstractions (factories/providers/managers) for small local logic.

### G) Noisy logging and narration

Remove logs that restate the line of code, are inconsistent with the module’s logging level, or spam hot paths.

**Rust (before):**
```rust
log::info!("Starting normalization");
let out = normalize_tag(tag);
log::info!("Finished normalization");
out
```

**Rust (after):**
```rust
normalize_tag(tag)
```

(Keep logs that support production debugging when the module’s convention calls for them.)

### H) Placeholder TODOs without a ticket/reference

Remove “TODO: handle edge cases” style notes that add no actionable guidance and are not aligned with repository practices.

### I) Unicode hazards and emoji noise in code/comments

Remove suspicious or unnecessary Unicode in **code and configs**, including:

- non-breaking spaces (`U+00A0`)
- zero-width characters (`U+200B`, `U+200D`)
- “smart quotes” (`“ ” ‘ ’`) in code/config
- homoglyphs in identifiers
- emojis in code comments/docs unless the repository explicitly uses them

**Python (before):**
```python
# ✅ Done! 🚀
name = "abc"  # zero-width space
```

**Python (after):**
```python
name = "abc"
```

(Do not “sanitize” legitimate localized/user-facing content unless it appears to be accidental.)

## Trust boundaries: when defensive checks are appropriate

Defensive checks are generally appropriate at **untrusted boundaries**, such as:

- request/CLI/env input handling
- parsing and decoding (JSON, CSV, protobuf, HTML, etc.)
- network/RPC boundaries
- filesystem reads/writes of external data
- third-party callbacks and plugin systems

Defensive checks are often slop within **trusted internal pipelines**, such as:

- post-validated domain objects
- post-auth/permission middleware
- post-schema validation
- internal-only transforms with strong invariants

When in doubt, follow existing patterns in the same module/subsystem.

## Workflow checklist

1. Identify the diff source (cached, working tree, or `main..HEAD`).
2. For each changed hunk:
   - Determine the intended behavior change.
   - Remove additions that are not required to achieve it.
   - Align with local style (naming, typing, error strategy, comment density).
3. Remove unused imports, dead code, and redundant helper layers introduced by the branch.
4. Keep changes minimal: avoid unrelated refactors.
5. Ensure changes still satisfy **AGENTS.md** (and other repo policies).
6. If repository tooling exists (formatters/linters/tests), avoid introducing new warnings.

## Final report requirement

At the end, output **only a 1–3 sentence summary** describing what you changed. No bullet points. No emojis. No extended explanation.

Example acceptable summary:
> Removed redundant input checks and log-and-rethrow blocks added in this branch, and inlined single-use helpers to match existing style. No functional behavior changes beyond the intended diff; all edits were confined to the branch’s modified hunks.

Review the source

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Get the skill: Price unconfirmed
Run it: Requirements have not been confirmed. Check the source for agent, API and service charges.
License: Apache-2.0
Price unconfirmed: We have not confirmed a price for this skill. Existing source and install links remain available.

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Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: Apache-2.0

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 41 GitHub stars
Stars/forks activity: 41 stars, 6 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: DeevsDeevs/agent-system
License: Apache-2.0
Version: Unknown
Last GitHub push: Jul 30, 2026
Registry updated: Oct 6, 2026
Instruction path: anti-ai-slop/SKILL.md @ 79de7729aad1

Version reported in registry metadata; check source releases before relying on it.

Quality

52/100

Needs review

Trust

60/100

Sandbox only

Audit

69/100

Needs review

Open full audit View eval report

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 41 GitHub stars
Stars/forks activity: 41 stars, 6 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

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This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

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More details

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      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 69,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 41 GitHub stars",
      "Stars/forks activity: 41 stars, 6 forks; issue activity unavailable in current metadata"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 52,
    "label": "Needs review"
  },
  "supply": {
    "track": "Coding and developer agents",
    "scenario": "Coding agents",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use anti-ai-slop in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 68/100 Manual review",
      "Audit: 69/100 Needs review",
      "Safety: 25/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "deevsdeevs-anti-ai-slop (anti-ai-slop)",
      "install_command": "npx skills add DeevsDeevs/agent-system --skill anti-ai-slop",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "deevsdeevs-anti-ai-slop",
      "task": "Use anti-ai-slop in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/deevsdeevs-anti-ai-slop",
    "api": "https://www.openagentskill.com/api/agent/skills/deevsdeevs-anti-ai-slop",
    "audit": "https://www.openagentskill.com/skills/deevsdeevs-anti-ai-slop/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=deevsdeevs-anti-ai-slop&task=Use%20anti-ai-slop%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-ai-slop%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20anti-ai-slop%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/deevsdeevs-anti-ai-slop/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/deevsdeevs-anti-ai-slop"
  }
}

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Creator: DeevsDeevs
Source: DeevsDeevs/agent-system
Indexed by: OpenAgentSkill community index

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Overview

Intent

Scope and diff source

Non-goals

What counts as AI slop

A) Comment and documentation bloat

B) Unnecessary defensive checks inside trusted codepaths

C) Try/catch / try blocks that add no value

D) Single-use variables and one-off helpers that should be inlined

E) Redundant checks/casts duplicated at caller and callee

F) Style drift and inconsistency with the file

G) Noisy logging and narration

H) Placeholder TODOs without a ticket/reference

I) Unicode hazards and emoji noise in code/comments

Trust boundaries: when defensive checks are appropriate

Workflow checklist

Final report requirement

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