comprehensive-research-agent

Structured thinking blocks document learnings, rationale, and gaps after each research step in multi-source literature reviews. They force agents to reveal their decision process, ensuring conclusions remain transparent and traceable to specific sources.

Failed tool calls during AI-assisted investigations are handled using explicit error recovery strategies. The workflow mandates error-aware rules that guide the agent through alternative actions while maintaining the integrity of the source-tracking log.

The best way to track sources across multiple tool interactions is enforcing a thinking trace that logs validation steps and decisions. This cross-source validation ensures evidence synthesis remains reliable and directly links conclusions to origins.

Yes, you can use this for evidence synthesis across different research domains. The workflow applies reusable thinking patterns to guide agents through three or more tool interactions, validating findings and preventing hallucinations regardless of the domain.

No specific dependencies are required to run error-aware research workflows. The skill operates independently, providing structured thinking blocks and explicit error handling rules to guide multi-source research tasks within existing AI agent setups.