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add-golden

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Curate and add documents to the golden dataset with multi-agent validation. Use when adding test data, creating golden datasets, saving examples.

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orchestkit

yonatangross/orchestkit

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yonatangross/orchestkit
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skills/add-golden/SKILL.md

Last Verified

January 25, 2026

Install Skill

Select agents to install to:

Scope:
npx add-skill https://github.com/yonatangross/orchestkit/blob/main/skills/add-golden/SKILL.md -a claude-code --skill add-golden

Installation paths:

Claude
.claude/skills/add-golden/
Powered by add-skill CLI

Instructions

# Add to Golden Dataset

Multi-agent curation workflow with quality score explanations, bias detection, and version tracking.

## Quick Start

```bash
/add-golden https://example.com/article
/add-golden https://arxiv.org/abs/2312.xxxxx
```

---

## Task Management (CC 2.1.16)

```python
# Create main curation task
TaskCreate(
  subject="Add to golden dataset: {url}",
  description="Multi-agent curation with quality explanation",
  activeForm="Curating document"
)

# Create subtasks for 9-phase process
phases = ["Fetch content", "Run quality analysis", "Explain scores",
          "Check bias", "Check diversity", "Validate", "Get approval",
          "Write to dataset", "Update version"]
for phase in phases:
    TaskCreate(subject=phase, activeForm=f"{phase}ing")
```

---

## Workflow Overview

| Phase | Activities | Output |
|-------|------------|--------|
| **1. Input Collection** | Get URL, detect content type | Document metadata |
| **2. Fetch and Extract** | Parse document structure | Structured content |
| **3. Quality Analysis** | 4 parallel agents evaluate | Raw scores |
| **4. Quality Explanation** | Explain WHY each score | Score rationale |
| **5. Bias Detection** | Check for bias in content | Bias report |
| **6. Diversity Check** | Assess dataset balance | Diversity metrics |
| **7. Validation** | Schema, duplicates, gates | Validation status |
| **8. Silver-to-Gold** | Promote or mark as silver | Classification |
| **9. Version Tracking** | Track changes, rollback | Version entry |

---

## Phase 1-2: Input and Extraction

Detect content type: article, tutorial, documentation, research_paper.

Extract: title, sections, code blocks, key terms, metadata (author, date).

---

## Phase 3: Parallel Quality Analysis (4 Agents)

Launch ALL agents in ONE message with `run_in_background=True`.

| Agent | Focus | Output |
|-------|-------|--------|
| code-quality-reviewer | Accuracy, coherence, depth, relevance | Quality scores |
| workflow-architect | Keyword dir

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