ag2ai Research Methodology
The Research Analyst agent follows a systematic methodology to produce reliable, well-sourced research reports.
Research phases
1. Scoping
Before any search begins, the agent defines:
- Topic boundaries -- What is in scope and what is not.
- Depth requirement -- Surface-level overview vs. deep technical analysis.
- Output expectations -- Report length, audience, and required sections.
If the user's request is ambiguous, the agent asks clarifying questions before proceeding.
2. Broad search
The agent uses WebSearch with multiple query variations to find a diverse set of sources:
- Rephrase the topic using synonyms and related terms.
- Search for both supporting and opposing viewpoints.
- Look for primary sources (research papers, official docs) and secondary sources (analysis, commentary).
- Target different content types: articles, documentation, forum discussions, code repositories.
3. Deep reading
For the most promising results, the agent uses WebFetch to read full pages and extract:
- Key statistics and data points.
- Direct quotes from domain experts.
- Methodology details (for research papers).
- Publication dates and author credentials.
4. Cross-referencing
Every factual claim is verified against at least two independent sources:
- If multiple sources agree, the claim is marked High confidence.
- If only one source supports it, the claim is marked Medium confidence with a note.
- If sources contradict each other, both positions are presented with context.
5. Synthesis
The agent identifies patterns across sources:
- Common themes and areas of consensus.
- Active debates and unresolved questions.
- Gaps in available information.
- Emerging trends that multiple sources hint at.
6. Report writing
The final report follows a fixed structure: Executive Summary, Key Findings, Detailed Analysis, Sources, and Confidence Assessment. Every factual claim includes an inline citation.
Source evaluation criteria
The agent ranks sources using these factors:
| Factor | Weight | Description |
|---|---|---|
| Authority | High | Is the author or organization a recognized expert? |
| Recency | High | When was the content published or last updated? |
| Evidence | Medium | Does the source cite its own references? |
| Objectivity | Medium | Does the source acknowledge limitations and counterarguments? |
| Corroboration | High | Do other independent sources agree? |
When to use local tools
If the research topic relates to code in the current project, the agent supplements web research with local analysis:
- Grep to find relevant patterns, imports, and usage.
- Read to examine specific files in detail.
- Glob to understand project structure.
- Bash to run commands like
git logfor project history.
This is especially useful for questions about the project's architecture, dependencies, or implementation details.