comprehensive-research-agent

Validate tool outputs and document reasoning across multi-step web research tasks.

Updated Feb 14, 2026
One-click install
npx skills add https://github.com/Shakudo-io/opencode-skills --skill comprehensive-research-agent-shakudo-io
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: comprehensive-research-agent
Source: https://github.com/Shakudo-io/opencode-skills/tree/main/context-optimization/examples/interleaved_thinking/generated_skills/comprehensive-research-agent
Command: npx skills add https://github.com/Shakudo-io/opencode-skills --skill comprehensive-research-agent-shakudo-io

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Research tasks often involve multiple tool calls, inconsistent validation, and opaque reasoning. This Skill provides structured protocols for thorough validation, explicit error recovery, and thinking transparency to improve reliability.

Core Features & Use Cases

  • Explicit validation at phase transitions to confirm tool outputs and source relevance.
  • Mandatory error acknowledgment and recovery strategies when tool calls fail.
  • Source tracing and cross-source validation to reduce hallucinations and support justified conclusions.
  • Structured thinking blocks that document insights, connections, gaps, and decision rationale.

Quick Start

Instruct the agent to validate each tool result, log any failures, and cross-check key claims against multiple sources before proceeding.

Frequently Asked Questions about comprehensive-research-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ensure transparent reasoning in multi-step research tasks?

To ensure transparent reasoning in multi-step research tasks, implement structured thinking blocks that document insights, connections, gaps, and decision rationale across three or more tool interactions. This enforces explicit validation at phase transitions to confirm tool outputs and source relevance.

What's the best way to prevent errors and hallucinations when validating web research sources?

The best way to prevent errors and hallucinations during web research is applying source tracing and cross-source validation to reduce unsupported claims. This requires explicit validation of tool outputs and cross-checking key claims against multiple sources before proceeding to the next phase.

How do I recover from tool failures during multi-tool research workflows?

Recover from tool failures during multi-tool research workflows by implementing mandatory error acknowledgment and explicit recovery strategies. This error-tolerant research approach logs failures and applies structured protocols to maintain reliability when tool calls fail.

When do I need explicit validation and cross-source verification for research workflows?

You need explicit validation and cross-source verification for research workflows involving three or more tool interactions where source reliability is critical. This process satisfies requirements for structured thinking blocks, source tracing, and documented decision rationale to ensure transparent reasoning.

Does this error-tolerant research approach work without external dependencies?

Yes, this error-tolerant research approach works without external dependencies. It provides structured internal protocols for thorough validation, explicit error recovery, and thinking transparency to improve reliability across multiple tool calls natively.

What are the limitations of using structured thinking blocks for multi-tool research?

A limitation of using structured thinking blocks for multi-tool research is the overhead required to document insights and decision rationale at every phase transition. This structured protocol slows down workflows that do not require explicit validation or cross-source verification.