tinyfish-io/agentql
Feb 2025 – Mar 2025
2 Months active
Languages Used
JavaScriptMarkdownPython
Technical Skills
AgentQL SDKAsynchronous ProgrammingCSV GenerationData AggregationData ExtractionExample Development
R L Nabors
PROFILE
R L Nabors
Rachel Nabors developed a cross-language Data Extraction Examples Suite for the tinyfish-io/agentql repository, delivering practical scripts in Python and JavaScript for news aggregation and Google Maps scraping. Their work demonstrated the AgentQL SDK’s capabilities in asynchronous programming, data extraction, and CSV generation, enabling seamless export pipelines for business workflows. Rachel also enhanced documentation by adding an Integrations page and updating the README to clarify compatibility with tools like Langchain and Zapier. The engineering focused on real-world use cases, clear commit traceability, and integration with workflow automation, providing depth and utility for both technical users and business stakeholders.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
427
Activity Months2
Your Network
5 people
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for tinyfish-io/agentql focusing on documenting integrations and improving tool discoverability.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for tinyfish-io/agentql focusing on documenting integrations and improving tool discoverability.
March 2025
February 2025
2 Commits • 1 Features
Feb 1, 2025Monthly summary for February 2025 focusing on business value and technical achievements for repo tinyfish-io/agentql. Key features delivered: - Data Extraction Examples Suite: News Aggregator and Google Maps Scraping. Introduces cross-language data extraction examples in Python and JavaScript, with CSV export capabilities and practical business use cases. Demonstrates AgentQL SDK usage and real-world data workflows. - Commits tied to feature delivery: - 75c7aecc8e21e9e782629a8a20f46b6161087282: Adds news aggregator example in Python and JavaScript (#120) - b9c2fd16c54061499a7239dc846990e0690a3493: Adds a map scraper example to python and JS example (#119) Major bugs fixed: - None reported this month. Overall impact and accomplishments: - Expanded library utility for data extraction in business contexts, enabling workshops and client demos with ready-to-run examples. - Strengthened cross-language support (Python & JavaScript) and clarified data export paths (CSV), improving integration with workflow tools like Langflow and Zapier. - Demonstrated end-to-end value from data extraction to export, enhancing adoption potential and showcasing practical capabilities of the AgentQL SDK. Technologies/skills demonstrated: - Python and JavaScript data extraction patterns, cross-language SDK usage, CSV export pipelines, and repository craftsmanship. - Clear commit traceability and alignment with business use cases.
February 2025
2 Commits • 1 Features
Feb 1, 2025Monthly summary for February 2025 focusing on business value and technical achievements for repo tinyfish-io/agentql. Key features delivered: - Data Extraction Examples Suite: News Aggregator and Google Maps Scraping. Introduces cross-language data extraction examples in Python and JavaScript, with CSV export capabilities and practical business use cases. Demonstrates AgentQL SDK usage and real-world data workflows. - Commits tied to feature delivery: - 75c7aecc8e21e9e782629a8a20f46b6161087282: Adds news aggregator example in Python and JavaScript (#120) - b9c2fd16c54061499a7239dc846990e0690a3493: Adds a map scraper example to python and JS example (#119) Major bugs fixed: - None reported this month. Overall impact and accomplishments: - Expanded library utility for data extraction in business contexts, enabling workshops and client demos with ready-to-run examples. - Strengthened cross-language support (Python & JavaScript) and clarified data export paths (CSV), improving integration with workflow tools like Langflow and Zapier. - Demonstrated end-to-end value from data extraction to export, enhancing adoption potential and showcasing practical capabilities of the AgentQL SDK. Technologies/skills demonstrated: - Python and JavaScript data extraction patterns, cross-language SDK usage, CSV export pipelines, and repository craftsmanship. - Clear commit traceability and alignment with business use cases.
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance86.6%
AI Usage33.4%
Skills & Technologies
Programming Languages
JavaScriptMarkdownPython
Technical Skills
AgentQL SDKAsynchronous ProgrammingCSV GenerationData AggregationData ExtractionDocumentationExample DevelopmentFile I/OPlaywrightWeb Scraping
Repositories Contributed To
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