Automate vendor-specific web search, extraction, and enrichment workflows with JSON output.
npx skills add https://github.com/Aevonix/colony-ai --skill parallel-cli-aevonix
Please help me install this Agent Skill. Skill: parallel-cli Source: https://github.com/Aevonix/colony-ai/tree/main/skills/research/parallel-cli Command: npx skills add https://github.com/Aevonix/colony-ai --skill parallel-cli-aevonix
Parallel CLI integration provides a vendor-specific workflow for advanced web search, extraction, enrichment, and monitoring, delivering structured results that complement Colony-native tools.
Run a non-interactive search with --json against a target query to begin.
High-intent search queries and answers about installing and using this skill.
Asynchronous web search workflows with JSON output are automated by submitting non-interactive search queries and polling for task status. This ensures structured, machine-readable results for long-running data gathering and extraction tasks.
Entity discovery and data enrichment involve extracting web search results and building richer context around them. This process surfaces structured datasets by automatically looking up and enhancing specific entities found across diverse web sources.
Parallel research tasks run asynchronously, allowing you to submit multiple queries and monitor their progress. You use status polling to track each long-running task and fetch enriched, predictable JSON results upon completion.
Yes, non-interactive CLI commands support structured data extraction by using the --json flag. This approach guarantees JSON-first outputs without requiring user interaction, making it ideal for repeatable automated workflows.
Monitoring changes across diverse web sources is handled through FindAll-like capabilities that track data shifts over time. This delivers structured, machine-readable datasets for continuous discovery and monitoring without manual intervention.
Asynchronous task management is needed for building agent knowledge bases when orchestrating parallel research runs. It allows you to submit multiple queries, poll for completion, and fetch enriched JSON results predictably.
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