command-center/omp-docs/agentic-web-research/research-effectiveness.md

type, title, description, tags, verified, timestamp

type	title	description	tags	verified	timestamp
concept	Research Effectiveness	Orchestrate a multi-step research loop — roles, credibility scoring, and when to stop.	agentic research orchestration credibility unverified	2026-08-28	2026-08-11

Research Effectiveness

One model call does not make good research. A research pipeline assigns roles, scores sources, and stops when it has enough. This page explains how to build one.

Add Structure With Roles

Split the work into roles. Each role has one job.

graph LR
    A[Researcher] --> B[Analyst]
    B --> C[Writer]
    C --> D[Critic]
    D -->|gaps found| A
    D -->|done| E[Final report]

Role	Job
Researcher	Search, extract pages, rank sources
Analyst	Extract facts, evaluate credibility
Writer	Synthesize and write the report
Critic	Find gaps and request follow-up

Use a Manager and a Search Agent

The strongest open recipe is a two-tier design:

• A manager agent reasons and plans. It uses code actions and a plan that it re-checks every few steps.
• A search agent does the web browsing. It has its own bounded tool set and step cap.

The search agent holds the browser tools: search, visit page, find on page, inspect files, and archive fallback. The manager reads results, decides what to follow next, and asks for a final answer when done.

This pattern powers open deep-research systems. The open reproduction scores about 55 percent on GAIA, below the closed OpenAI version at 67 percent, but it runs fully on your own stack.

Score Source Credibility

Score each source on a small set of signals:

• Domain authority.
• Content freshness.
• Source diversity (independent sources agree).
• Whether other sources confirm the claim.

Cross-reference each fact. If two independent sources agree, the fact is stronger.

Keep Context Small

Never pass a full page to the model.

• Convert HTML to Markdown and strip scripts and navigation.
• Split long pages into viewports and show one chunk at a time.
• Cap file text at a fixed size, for example 100,000 characters.
• Filter content before the model sees it.

Smaller context means a faster loop and a lower chance of confusion.

Stop Hallucinated Citations

An agent can invent a source. Guard against it:

1. The agent returns answers with structured citations.
2. The manager re-fetches each cited URL.
3. If a citation fails, the agent re-searches with a modified query.

Use a web archive as a fallback for dead links.

Adapt the Search

Do not follow every link. Follow the links that the question needs. Stop when the confidence threshold passes. Tools such as Crawl4AI expose an adaptive crawler that reports its own confidence.

Choose an Orchestration Tool

Tool	Best for	Notes
CrewAI	Role-based multi-agent work	Sequential or hierarchical processes
LangGraph	Stateful, long-running research	Durable execution, human in the loop
SmolAgents	Simple code-based agents	MCP support, manager + search agent
Qwen-Agent	Qwen model + MCP tools	Best integration with Qwen3

Pi already runs a similar model with its parallel researcher and scout subagents.

The Finish Rule

Research must end. Stop when any one is true:

1. Two or more independent sources agree on the answer.
2. The retrieval budget is spent.
3. The required confidence is met for every claim.

Report gaps honestly. Do not invent a source to fill one.

Failure Modes and Guardrails

Agentic loops fail in predictable ways. Add guardrails up front.

Failure	Guardrail
Hallucinated citation	Cite structured objects, then re-fetch each URL
Search engine block	Respect retry-after, use adaptive rate limiting, read the ban time
Infinite re-search	Cap search rounds, reject near-duplicate queries, re-plan every few steps
Context overflow	Filter content before the model sees it, track the token budget

Citations

• Smolagents open deep research: https://huggingface.co/blog/open-deep-research
• Smolagents multiagents guide: https://huggingface.co/docs/smolagents/examples/multiagents
• CrewAI repository: https://github.com/crewAIInc/crewAI
• CrewAI documentation: https://docs.crewai.com/
• LangGraph repository: https://github.com/langchain-ai/langgraph
• Crawl4AI documentation: https://docs.crawl4ai.com

See Also

• Agentic Search Best Practices — The loop this orchestrates.
• Open Models for Web Use — The model that runs each role.