deep-research

name	deep-research
description	Pipeline de pesquisa profunda com multiplos agentes em paralelo. Gera relatorios em markdown com citacoes e protocolo anti-alucinacao. Use para analises comparativas, investigacoes de mercado e pesquisas abrangentes.
license	Apache-2.0
compatibility	Requires internet access
allowed-tools	Bash Read Edit Write WebFetch WebSearch Agent Glob Grep
metadata	{"author":"vector-labs","version":"1.0"}
tags	["research","analysis"]
complexity	advanced
featured	true

Deep Research

Agent-orchestrated research pipeline. Takes input text, decomposes into parallel agent tasks, synthesizes results into a citation-backed report.

Context budget: Orchestrator stays lean. Agents write to files, return summaries. Synthesis is delegated to a sub-agent. NEVER read agent output files or reference files into orchestrator context — pass paths to sub-agents. NEVER use run_in_background — it causes TaskOutput to return full agent logs. If context approaches limit before synthesis, the research is lost.

Workflow

1. Analyze Input

Classify the input:

• Question: Direct research question → extract core topic + angles
• Brief: Context document with research directive → extract what to investigate
• Seed context: Background text that needs expansion → identify knowledge gaps

Determine complexity (drives agent count):

• Focused (3 agents): Single topic, clear boundaries
• Broad (4-5 agents): Multi-faceted topic, comparison, or trend analysis

2. Decompose into Agent Tasks

Break research into 3-5 independent investigation angles. Each angle becomes a Task agent.

Decomposition heuristics:

• One angle per distinct sub-question or perspective
• Separate factual retrieval from opinion/analysis sources
• Include at least one critical/contrarian angle
• If project context is relevant, dedicate one agent to local analysis

Agent types (see agent-templates for full prompts):

Type	Tools	Use when
web-researcher	WebSearch, WebFetch	External facts, data, current info
local-analyst	Grep, Read, Glob	Project files, meeting notes, internal docs
deep-diver	WebSearch, WebFetch	Single source/topic requiring multi-step investigation

3. Deploy Agents (Parallel)

CRITICAL: Launch ALL agents in a single message with multiple Task tool calls.

CRITICAL: Do NOT use . Launch all agents as parallel Task calls in a single message. They execute concurrently, and each returns ONLY the agent's final message (the 3-5 line summary). Background agents write full conversation logs to output files — reading those with TaskOutput will overflow orchestrator context.