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feat: add clawhub skill badge (MigoXLab#374)
* fix: update agent artical fact check example * add clawhub skill badge
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‎README.md‎

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<a href="https://mseep.ai/app/dataeval-dingo"><img src="https://mseep.net/pr/dataeval-dingo-badge.png" alt="MseeP.ai Security Assessment Badge" height="20"></a>
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<a href="https://deepwiki.com/MigoXLab/dingo"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
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<a href="https://archestra.ai/mcp-catalog/dataeval__dingo"><img src="https://archestra.ai/mcp-catalog/api/badge/quality/DataEval/dingo" alt="Trust Score"></a>
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<a href="https://clawhub.ai/e06084/dingo"><img src="https://img.shields.io/badge/ClawHub-Skill-orange?logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI+PHRleHQgeT0iMTgiIGZvbnQtc2l6ZT0iMTYiPvCfpp48L3RleHQ+PC9zdmc+" alt="ClawHub Skill"></a>
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</p>
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</div>

‎README_ja.md‎

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<a href="https://mseep.ai/app/dataeval-dingo"><img src="https://mseep.net/pr/dataeval-dingo-badge.png" alt="MseeP.ai Security Assessment Badge" height="20"></a>
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<a href="https://deepwiki.com/MigoXLab/dingo"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
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<a href="https://archestra.ai/mcp-catalog/dataeval__dingo"><img src="https://archestra.ai/mcp-catalog/api/badge/quality/DataEval/dingo" alt="Trust Score"></a>
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<a href="https://clawhub.ai/e06084/dingo"><img src="https://img.shields.io/badge/ClawHub-Skill-orange?logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI+PHRleHQgeT0iMTgiIGZvbnQtc2l6ZT0iMTYiPvCfpp48L3RleHQ+PC9zdmc+" alt="ClawHub Skill"></a>
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</p>
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</div>

‎README_zh-CN.md‎

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<a href="https://mseep.ai/app/dataeval-dingo"><img src="https://mseep.net/pr/dataeval-dingo-badge.png" alt="MseeP.ai 安全评估徽章" height="20"></a>
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<a href="https://deepwiki.com/MigoXLab/dingo"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
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<a href="https://archestra.ai/mcp-catalog/dataeval__dingo"><img src="https://archestra.ai/mcp-catalog/api/badge/quality/DataEval/dingo" alt="Trust Score"></a>
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<a href="https://clawhub.ai/e06084/dingo"><img src="https://img.shields.io/badge/ClawHub-Skill-orange?logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI+PHRleHQgeT0iMTgiIGZvbnQtc2l6ZT0iMTYiPvCfpp48L3RleHQ+PC9zdmc+" alt="ClawHub Skill"></a>
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</p>
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</div>

‎examples/agent/agent_article_fact_checking_example.py‎

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- TAVILY_API_KEY: (Optional) For web search verification
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"""
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import json
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import os
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import tempfile
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from dingo.config import InputArgs
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from dingo.exec import Executor
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print("WARNING: TAVILY_API_KEY not set - web search verification will be limited")
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print(" Set it with: export TAVILY_API_KEY='your-api-key'")
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# Read the complete article (Markdown input)
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article_path = "test/data/blog_article_full.md"
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article_path = "test/data/factcheck_article.jsonl"
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if not os.path.exists(article_path):
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print(f"ERROR: Article file not found: {article_path}")
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return 1
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with open(article_path, 'r', encoding='utf-8') as f:
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article_content = f.read()
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# Wrap article in JSONL so Executor treats it as a single Data object.
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temp_jsonl = tempfile.NamedTemporaryFile(mode='w', suffix='.jsonl', delete=False, encoding='utf-8')
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temp_jsonl.write(json.dumps({"content": article_content}, ensure_ascii=False) + '\n')
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temp_jsonl.close()
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# Configuration for ArticleFactChecker
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config = {
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"input_path": temp_jsonl.name,
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"input_path": article_path,
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"dataset": {
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"source": "local",
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"format": "jsonl"
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print("Artifact output: outputs/article_factcheck_<timestamp>/")
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print("=" * 70)
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# Create input args and executor
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input_args = InputArgs(**config)
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executor = Executor.exec_map["local"](input_args)
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try:
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# Execute fact-checking
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print("\nExecuting agent-based fact-checking...\n")
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result = executor.execute()
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# Display results
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print("\n" + "=" * 70)
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print("FACT-CHECKING RESULTS")
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print("=" * 70)
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if result:
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print(f"\nTotal items evaluated: {result.total}")
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print(f"Passed: {result.num_good} | Issues found: {result.num_bad}")
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if result.score:
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print(f"Overall score: {result.score:.2%}")
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if result.type_ratio:
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print("\nIssue breakdown:")
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for field_key, type_counts in result.type_ratio.items():
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for label, count in type_counts.items():
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print(f" [{field_key}] {label}: {count}")
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print("\nFact-checking complete!")
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print(f"\nDingo standard output: {input_args.output_path}/")
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print(" |-- summary.json (aggregated statistics)")
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print(" +-- content/<LABEL>.jsonl (results grouped by quality label)")
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print("\nIntermediate artifacts: outputs/article_factcheck_<timestamp>_<uuid>/")
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print(" |-- article_content.md (original Markdown article)")
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print(" |-- claims_extracted.jsonl (extracted claims, one per line)")
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print(" |-- claims_verification.jsonl (per-claim verification details)")
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print(" +-- verification_report.json (full structured report)")
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print("\nNote: Override artifact path with agent_config.output_path in config")
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finally:
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try:
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os.unlink(temp_jsonl.name)
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except OSError:
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pass
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print("\nExecuting agent-based fact-checking...\n")
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result = executor.execute()
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print("\n" + "=" * 70)
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print("FACT-CHECKING RESULTS")
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print("=" * 70)
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if result:
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print(f"\nTotal items evaluated: {result.total}")
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print(f"Passed: {result.num_good} | Issues found: {result.num_bad}")
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if result.score:
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print(f"Overall score: {result.score:.2%}")
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if result.type_ratio:
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print("\nIssue breakdown:")
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for field_key, type_counts in result.type_ratio.items():
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for label, count in type_counts.items():
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print(f" [{field_key}] {label}: {count}")
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print("\nFact-checking complete!")
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print(f"\nDingo standard output: {input_args.output_path}/")
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print(" |-- summary.json (aggregated statistics)")
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print(" +-- content/<LABEL>.jsonl (results grouped by quality label)")
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print("\nIntermediate artifacts: outputs/article_factcheck_<timestamp>_<uuid>/")
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print(" |-- article_content.md (original Markdown article)")
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print(" |-- claims_extracted.jsonl (extracted claims, one per line)")
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print(" |-- claims_verification.jsonl (per-claim verification details)")
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print(" +-- verification_report.json (full structured report)")
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print("\nNote: Override artifact path with agent_config.output_path in config")
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return 0
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