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anti-slop

Comprehensive Anti-AI Slop enforcement guide. Updated to include token efficiency and code gardening / Panduan penegakan anti-AI slop komprehensif. Diperbarui dengan efisiensi token dan perawatan kode.

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Precio sin confirmar★ 73 Estrellas de GitHubRegistro actualizado · 30 sept 2026agent-skill

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Anti-Slop, Token Efficiency & Code Gardening Protocol (2026 Edition)

English | Bahasa Indonesia

English

Description & Trigger Conditions

The absolute zero-tolerance standard against AI slop, bloated context, and architectural decay. AI slop manifests as conversational pleasantries, lazy placeholders, speculative over-engineering, decorative comments, and vague buzzwords. This skill enforces rigorous anti-slop rules, token-saving compression, and code gardening across the engineering lifecycle. Triggers: Any code generation/modification, automated reviews, long-running sessions, explicit "be concise/minimal" requests, or when a codebase exhibits "AI smell" (inconsistencies, duplication, dead code).

The 5 Pillars of AI Slop Elimination

Pillar 1: Conversational & Sycophancy Slop

🔴 Forbidden: Preambles ("Certainly! I'd be happy to help"), prompt echoing, apology loops, trailing motivational fluff.
✅ Standard: Imperative, code-first communication. Zero filler.

Pillar 2: Placeholder & Truncation Slop ("Lazy LLM")

🔴 Forbidden: // TODO: implement, // ... rest of code, or returning mock arrays when production features are requested.
✅ Standard: Output must be 100% complete, functional, and production-ready.

Pillar 3: Speculative & Decorative Over-Engineering Slop

🔴 Forbidden: Creating factory patterns (IUserServiceFactoryProvider) for single implementations, triple-validated defensive code when TypeScript/Zod guarantee type safety.
✅ Standard: YAGNI (You Aren't Gonna Need It). Write the simplest direct implementation. Trust the types.

Pillar 4: Obvious & Decorative Comment Slop

🔴 Forbidden: Narrating syntax line-by-line (e.g., // Increment count by 1 \n setCount(count + 1);).
✅ Standard: Comments explain WHY (architectural decisions, business constraints), never WHAT.

Pillar 5: Buzzword & Artifact Slop

🔴 Forbidden: Documents filled with generic marketing jargon ("seamless integration", "robust synergy") with zero technical density.
✅ Standard: High technical density with explicit schemas, route tables, column types, and verifiable NFR latency budgets.

Token Efficiency & Compression Protocol

1. Response Compression Rules

No preamble/restatement/summaries: Show code immediately, explain briefly after.
Diff format: For file edits, show only changed lines.
Bullet > prose: Use 1-sentence rationales over paragraphs.

2. Context Window Budget Awareness (200K Context)

System prompt + skills: ~15K | Conversation history: ~50K | File reads: ~100K | Response: ~35K

Summarize large files mentally; view_file only specific sections. Create a checkpoint with session-memory-manager when near full.

3. Tool Call Minimization & First Draft Quality

Read multiple files in parallel.
Use grep_search over full reads.
Generate correct, production-ready code with inline error handling on the first try. Avoid edit-retry cycles.

Legacy Code Gardening Protocol

1. Context Drift Analysis & Code Smells

Inconsistent Styles: Mixed async/await vs .then(), variable namings (userId vs user_id). Fix with Prettier/ESLint rules.
Bloated Components: 5+ states, 10+ props, 20+ imports. Apply Single Responsibility and split them.
Dependency Creep: Use npx depcheck for unused dependencies and npx bundle-phobia-cli for sizing.
Graveyard of Dead Utilities: Use semantic search/grep to find and remove 0-usage exported functions.

2. 4-Phase Gardening Protocol

Discovery: Map file tree, find bloated files, duplicated logic, unused exports, and style drift.
Triage: Categorize into Critical (bugs/data loss), High (diverging duplicates), Medium (smells), Low (style).
Systematic Refactoring: Start smallest first. Remove dead code, extract duplicates, simplify abstractions, standardize names, add tests.
Prevention: Add strict ESLint rules, depcheck in CI, and architecture tests.

Automated Anti-Slop Audit Script

Run scripts/check-anti-slop.js in CI to detect placeholders (// ...), unfinished stubs (TODO:), mock data in prod, and syntax narration (// increment). Fail builds if AI slop is detected.

Bahasa Indonesia

Deskripsi & Kondisi Pemicu

Standar nol-toleransi terhadap AI slop, pemborosan token, dan pembusukan arsitektur. AI slop muncul sebagai basa-basi, placeholder, over-engineering spekulatif, dan komentar dekoratif. Skill ini menegakkan anti-slop, kompresi respons, dan perawatan kode (code gardening). Pemicu: Pembuatan/modifikasi kode, review otomatis, sesi panjang, permintaan respons ringkas, atau saat codebase menunjukkan "AI smell" (inkonsistensi, duplikasi, kode mati).

5 Pilar Utama Pembasmian AI Slop

Pilar 1: Eliminasi Basa-Basi Percakapan - Dilarang menggunakan pengantar atau pengulangan instruksi. Harus code-first dan tanpa basa-basi.
Pilar 2: Larangan Placeholder & Truncation ("Lazy LLM") - Dilarang keras menggunakan // TODO atau memotong kode. Wajib 100% lengkap dan siap produksi.
Pilar 3: Anti Over-Engineering Spekulatif - Hindari factory pattern atau layer ekstra tanpa alasan. Jangan validasi ganda jika Zod/TypeScript sudah menanganinya. Terapkan YAGNI.
Pilar 4: Eliminasi Komentar Sintaksis - Jangan menarasikan baris kode (mis. // tambah satu). Komentar hanya untuk menjelaskan MENGAPA (alasan bisnis/arsitektur).
Pilar 5: Eliminasi Slop Dokumen & Buzzword - Hindari kata-kata marketing kosong. Gunakan densitas teknis tinggi dengan skema pasti dan metrik konkret.

Protokol Efisiensi & Kompresi Token

Kompresi Respons: Gunakan format diff untuk kode. Penjelasan menggunakan poin 1-kalimat daripada paragraf. Tanpa basa-basi.
Budget 200K Konteks: Batasi baca file penuh; gunakan grep_search. Buat checkpoint dengan session-memory-manager jika token menipis.
Efisiensi Tool: Baca file paralel, temukan konten spesifik dengan grep. Hasilkan draf pertama yang siap produksi tanpa siklus edit berulang.

Protokol Berkebun Kode Warisan (Code Gardening)

Analisis Context Drift: Perbaiki inkonsistensi gaya (contoh: async vs then, userId vs user_id) dengan ESLint/Prettier.
Komponen Membengkak: Pecah komponen yang memiliki >5 state, >10 prop, atau >20 impor berdasarkan Tanggung Jawab Tunggal.
Utilitas Mati & Dependensi: Hapus fungsi tanpa penggunaan. Gunakan npx depcheck untuk package tidak terpakai dan bundle-phobia-cli untuk ukuran.
Protokol 4 Fase:
- Discovery: Petakan duplikasi dan kode mati.
- Triage: Kategorikan Kritis hingga Rendah.
- Refactoring: Hapus kode mati, ekstrak duplikat, sederhanakan abstraksi, tambah test.
- Prevention: Tambahkan ESLint strict, depcheck CI, dan uji arsitektur.

Orchestration & Integration

zero-to-prod-orchestrator: Anti-slop checks at architectural and deployment phases.
session-memory-manager: Context resets when token budgets approach limits.
scalability-clean-code: Enforces SOLID boundaries against speculative over-engineering.
autonomous-tdd-debugger: Validates execution completeness over mock/stub code.
coderabbit & brainstorming: Clean PR reviews and dense documentation.
dependency-upgrade-migrator: Integrates with dependency audits (depcheck).

Ver fuente ↗

Metadatos del archivo

name: anti-slop
description: "Comprehensive Anti-AI Slop enforcement guide. Updated to include token efficiency and code gardening / Panduan penegakan anti-AI slop komprehensif. Diperbarui dengan efisiensi token dan perawatan kode."
author: "Roedy Rustam"

version: "3.0.0"

Ver texto original

---
name: anti-slop
description: "Comprehensive Anti-AI Slop enforcement guide. Updated to include token efficiency and code gardening / Panduan penegakan anti-AI slop komprehensif. Diperbarui dengan efisiensi token dan perawatan kode."
author: "Roedy Rustam"

version: "3.0.0"
---

# Anti-Slop, Token Efficiency & Code Gardening Protocol (2026 Edition)

[English](#english) | [Bahasa Indonesia](#bahasa-indonesia)

---

<a name="english"></a>
## English

### Description & Trigger Conditions
The absolute zero-tolerance standard against AI slop, bloated context, and architectural decay. AI slop manifests as conversational pleasantries, lazy placeholders, speculative over-engineering, decorative comments, and vague buzzwords. This skill enforces rigorous anti-slop rules, token-saving compression, and code gardening across the engineering lifecycle.
Triggers: Any code generation/modification, automated reviews, long-running sessions, explicit "be concise/minimal" requests, or when a codebase exhibits "AI smell" (inconsistencies, duplication, dead code).

---

## The 5 Pillars of AI Slop Elimination

### Pillar 1: Conversational & Sycophancy Slop
- **🔴 Forbidden**: Preambles ("Certainly! I'd be happy to help"), prompt echoing, apology loops, trailing motivational fluff.
- **✅ Standard**: Imperative, code-first communication. Zero filler. 

### Pillar 2: Placeholder & Truncation Slop ("Lazy LLM")
- **🔴 Forbidden**: `// TODO: implement`, `// ... rest of code`, or returning mock arrays when production features are requested.
- **✅ Standard**: Output must be 100% complete, functional, and production-ready.

### Pillar 3: Speculative & Decorative Over-Engineering Slop
- **🔴 Forbidden**: Creating factory patterns (`IUserServiceFactoryProvider`) for single implementations, triple-validated defensive code when TypeScript/Zod guarantee type safety.
- **✅ Standard**: YAGNI (You Aren't Gonna Need It). Write the simplest direct implementation. Trust the types.

### Pillar 4: Obvious & Decorative Comment Slop
- **🔴 Forbidden**: Narrating syntax line-by-line (e.g., `// Increment count by 1 \n setCount(count + 1);`).
- **✅ Standard**: Comments explain WHY (architectural decisions, business constraints), never WHAT.

### Pillar 5: Buzzword & Artifact Slop
- **🔴 Forbidden**: Documents filled with generic marketing jargon ("seamless integration", "robust synergy") with zero technical density.
- **✅ Standard**: High technical density with explicit schemas, route tables, column types, and verifiable NFR latency budgets.

---

## Token Efficiency & Compression Protocol

### 1. Response Compression Rules
- **No preamble/restatement/summaries**: Show code immediately, explain briefly after.
- **Diff format**: For file edits, show only changed lines.
- **Bullet > prose**: Use 1-sentence rationales over paragraphs.

### 2. Context Window Budget Awareness (200K Context)
```text
System prompt + skills: ~15K | Conversation history: ~50K | File reads: ~100K | Response: ~35K
```
- Summarize large files mentally; `view_file` only specific sections. Create a checkpoint with `session-memory-manager` when near full.

### 3. Tool Call Minimization & First Draft Quality
- Read multiple files in parallel.
- Use `grep_search` over full reads.
- Generate correct, production-ready code with inline error handling on the first try. Avoid edit-retry cycles.

---

## Legacy Code Gardening Protocol

### 1. Context Drift Analysis & Code Smells
- **Inconsistent Styles**: Mixed `async/await` vs `.then()`, variable namings (`userId` vs `user_id`). Fix with Prettier/ESLint rules.
- **Bloated Components**: 5+ states, 10+ props, 20+ imports. Apply Single Responsibility and split them.
- **Dependency Creep**: Use `npx depcheck` for unused dependencies and `npx bundle-phobia-cli` for sizing.
- **Graveyard of Dead Utilities**: Use semantic search/grep to find and remove 0-usage exported functions.

### 2. 4-Phase Gardening Protocol
1. **Discovery**: Map file tree, find bloated files, duplicated logic, unused exports, and style drift.
2. **Triage**: Categorize into Critical (bugs/data loss), High (diverging duplicates), Medium (smells), Low (style).
3. **Systematic Refactoring**: Start smallest first. Remove dead code, extract duplicates, simplify abstractions, standardize names, add tests.
4. **Prevention**: Add strict ESLint rules, `depcheck` in CI, and architecture tests.

---

## Automated Anti-Slop Audit Script
Run `scripts/check-anti-slop.js` in CI to detect placeholders (`// ...`), unfinished stubs (`TODO:`), mock data in prod, and syntax narration (`// increment`). Fail builds if AI slop is detected.

---

<a name="bahasa-indonesia"></a>
## Bahasa Indonesia

### Deskripsi & Kondisi Pemicu
Standar nol-toleransi terhadap AI slop, pemborosan token, dan pembusukan arsitektur. AI slop muncul sebagai basa-basi, placeholder, over-engineering spekulatif, dan komentar dekoratif. Skill ini menegakkan anti-slop, kompresi respons, dan perawatan kode (code gardening).
Pemicu: Pembuatan/modifikasi kode, review otomatis, sesi panjang, permintaan respons ringkas, atau saat codebase menunjukkan "AI smell" (inkonsistensi, duplikasi, kode mati).

---

### 5 Pilar Utama Pembasmian AI Slop

1. **Pilar 1: Eliminasi Basa-Basi Percakapan** - Dilarang menggunakan pengantar atau pengulangan instruksi. Harus *code-first* dan tanpa basa-basi.
2. **Pilar 2: Larangan Placeholder & Truncation ("Lazy LLM")** - Dilarang keras menggunakan `// TODO` atau memotong kode. Wajib 100% lengkap dan siap produksi.
3. **Pilar 3: Anti Over-Engineering Spekulatif** - Hindari *factory pattern* atau layer ekstra tanpa alasan. Jangan validasi ganda jika Zod/TypeScript sudah menanganinya. Terapkan YAGNI.
4. **Pilar 4: Eliminasi Komentar Sintaksis** - Jangan menarasikan baris kode (mis. `// tambah satu`). Komentar hanya untuk menjelaskan MENGAPA (alasan bisnis/arsitektur).
5. **Pilar 5: Eliminasi Slop Dokumen & Buzzword** - Hindari kata-kata marketing kosong. Gunakan densitas teknis tinggi dengan skema pasti dan metrik konkret.

---

### Protokol Efisiensi & Kompresi Token

- **Kompresi Respons**: Gunakan format diff untuk kode. Penjelasan menggunakan poin 1-kalimat daripada paragraf. Tanpa basa-basi.
- **Budget 200K Konteks**: Batasi baca file penuh; gunakan `grep_search`. Buat checkpoint dengan `session-memory-manager` jika token menipis.
- **Efisiensi Tool**: Baca file paralel, temukan konten spesifik dengan grep. Hasilkan draf pertama yang siap produksi tanpa siklus edit berulang.

---

### Protokol Berkebun Kode Warisan (Code Gardening)

1. **Analisis Context Drift**: Perbaiki inkonsistensi gaya (contoh: `async` vs `then`, `userId` vs `user_id`) dengan ESLint/Prettier.
2. **Komponen Membengkak**: Pecah komponen yang memiliki >5 state, >10 prop, atau >20 impor berdasarkan Tanggung Jawab Tunggal.
3. **Utilitas Mati & Dependensi**: Hapus fungsi tanpa penggunaan. Gunakan `npx depcheck` untuk package tidak terpakai dan `bundle-phobia-cli` untuk ukuran.
4. **Protokol 4 Fase**:
   - *Discovery*: Petakan duplikasi dan kode mati.
   - *Triage*: Kategorikan Kritis hingga Rendah.
   - *Refactoring*: Hapus kode mati, ekstrak duplikat, sederhanakan abstraksi, tambah test.
   - *Prevention*: Tambahkan ESLint strict, depcheck CI, dan uji arsitektur.

---

## Orchestration & Integration
- `zero-to-prod-orchestrator`: Anti-slop checks at architectural and deployment phases.
- `session-memory-manager`: Context resets when token budgets approach limits.
- `scalability-clean-code`: Enforces SOLID boundaries against speculative over-engineering.
- `autonomous-tdd-debugger`: Validates execution completeness over mock/stub code.
- `coderabbit` & `brainstorming`: Clean PR reviews and dense documentation.
- `dependency-upgrade-migrator`: Integrates with dependency audits (`depcheck`).

Revisar el código fuente

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Obtener el skill: Precio sin confirmar
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Licencia: MIT
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Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →

Fuente del skill registrada

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Revisar antes de instalar: Evitar instalación automática

Licencia: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Falta aprobación de revisión por IA
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 73 GitHub stars
Stars/forks activity: 73 stars, 17 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

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Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

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Repositorio fuente: roedyrustam/vibes-plug
Licencia: MIT
Versión: 3.0.0
Último push de GitHub: 29 sept 2026
Registro actualizado: 30 sept 2026
Ruta de instrucciones: skills/anti-slop/SKILL.md @ 99f27057e0f7

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

60/100

Prometedor

Confianza

63/100

Solo sandbox

Auditoría

74/100

Requiere revisión

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Dependency or permission surface needs review
Permission surface may require sandboxing
Falta aprobación de revisión por IA
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 73 GitHub stars
Stars/forks activity: 73 stars, 17 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

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  "trust": {
    "score": 71,
    "label": "Manual review",
    "version": "trust-score-v4",
    "install_policy": "block",
    "evidence": {
      "stars": "73 GitHub stars",
      "repoActivity": "73 stars, 17 forks",
      "lastPushed": "14d since push",
      "license": "MIT",
      "repository": "https://github.com/roedyrustam/vibes-plug/tree/main/skills/anti-slop",
      "install": "npx skills add roedyrustam/vibes-plug --skill anti-slop",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "design-creative",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 73 GitHub stars",
      "Stars/forks activity: 73 stars, 17 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"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "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": 74,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "AI review approval is missing",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 73 GitHub stars",
      "Stars/forks activity: 73 stars, 17 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "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": 60,
    "label": "Promising"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "14d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "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-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: 71/100 Manual review",
      "Audit: 74/100 Needs review",
      "Safety: 34/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "roedyrustam-anti-slop (anti-slop)",
      "install_command": "npx skills add roedyrustam/vibes-plug --skill anti-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": "roedyrustam-anti-slop",
      "task": "Use anti-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/roedyrustam-anti-slop",
    "api": "https://www.openagentskill.com/api/agent/skills/roedyrustam-anti-slop",
    "audit": "https://www.openagentskill.com/skills/roedyrustam-anti-slop/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=roedyrustam-anti-slop&task=Use%20anti-slop%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20anti-slop%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20anti-slop%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/roedyrustam-anti-slop/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/roedyrustam-anti-slop"
  }
}

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Creador: roedyrustam
Fuente: roedyrustam/vibes-plug
Indexado por: Índice comunitario de OpenAgentSkill

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