Files
command-center/omp-docs/agentic-web-research/research-effectiveness.md
Frank 8b87b5ae1a docs(dedupe): one owner for the finish rule, and the Gitea index routes instead of restating
Two independent copies of the same law, and each page cited its own numbers. The finish rule —
stop when independent sources agree, when the retrieval budget is spent, or when every claim is
met; report gaps, never invent a source — stood in full in `agentic-search-best-practices.md`
(with the loop caps: 20 steps, re-plan every 4) and again in `research-effectiveness.md` without
them. The operational page owns it; the measurement page keeps the pointer and the one thing
that is its business, which is that unbounded loops are why "infinite re-search" is a named
failure mode.

`tools/gitea/index.md` was a second copy of its own directory: an architecture table, a
management command table, a data-persistence path table and a boot-persistence paragraph, every
one of them a subset of `architecture.md`, `management.md` and `data-persistence.md` — verified
line by line before cutting, including the two facts that looked unique to the index (the
`dns_enabled: false` default network, the `/opt/gitea` leftover) and turn out to be owned
upstream with more detail. The index now answers "which page owns my question" and gives three
one-line orientation facts. Gitea's live version was re-read while I was in there: still 1.27.3.

Refs #64
2026-10-21 02:24:11 -07:00

4.8 KiB

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.

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

The rule itself — stop when independent sources agree, when the retrieval budget is spent, or when every claim has the required confidence, and report the gaps instead of inventing a source — is owned by Agentic Search Best Practices, the page an agent reads before it starts a loop. What belongs here is the measurement: unbounded loops are why "infinite re-search" is a named failure mode in the next section.

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

See Also