Enterprise Data Retrieval Skill
Overview
This skill provides utility functions for searching and extracting information from enterprise product data files. It discovers the data schema at runtime rather than assuming fixed field names or structures.
End-to-End Usage
pythonimport sys sys.path.insert(0, '/app/environment/skills/evo-enterprise-data-retrieval/scripts') from utils import run_end_to_end, validate_answer # Run end-to-end: reads questions, searches data, writes answer.json result = run_end_to_end( question_path='/root/question.txt', data_dir='/root/DATA', output_path='/root/answer.json' ) # Validate the output errors = validate_answer('/root/answer.json') assert len(errors) == 0, f"Validation errors: {errors}" print("Done! Answer written to /root/answer.json")
Available Functions
load_product_data(product_name, data_dir)- Load a product data fileload_employee_data(data_dir)- Load employee metadatasearch_slack(product_data, keywords)- Search messaging data by keywordsfind_document_authors_and_reviewers(product_data, doc_type)- Find authors and reviewers for a document type across all available sourcesfind_competitor_insights(product_data)- Find team members who discussed competitor strengths/weaknessesfind_competitor_demo_urls(product_data)- Find external demo URLs for competitor productscreate_answer(answers_dict, output_path)- Write answer file with proper formatrun_end_to_end(question_path, data_dir, output_path)- Full pipeline from questions to answersvalidate_answer(output_path)- Validate answer file format and constraints
Key Patterns
- Document authors: found in document metadata author fields
- Document reviewers: found in messaging feedback and transcript participant lists
- Competitor insights: initiated by messages introducing competitor products for discussion
- Demo URLs: external URLs containing "demo" (filtered from internal URLs)


