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CrewAI Sequential Research Crew

Self-ReportedCurated

Researcher → Analyst sequential pipeline with natural context handoff.

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Curated from CrewAI Docs — First Crew — not claimed by or endorsed by the organization. Metrics cited only as the source states. Absent metrics render as [unknown].

Recent activity

Version cuts and proof, newest first — the living track record.

  1. Artifact · CrewAI sequential crew pattern documented in official docs2y ago

Spec sheet

The benchmark fields — designed for comparison across teams.

Topology
Pipeline
Agent count
2
Platform
CrewAI
Runs on
CrewAI ×2
Industries
researchcontent
Task kinds
researchreport-writinganalysis
Trust tier
Self-Reported
Proof entries
1

Topology & roster

Pipeline

Sequential pipeline. Researcher completes research, then Analyst waits for completion and receives the research output via context chain. Higher-level Flow manages state and decides what to do next, delegating complex subtasks to Crews.

System wiring

Typical Pipeline layout — schematic, not verified wiring
Typical role-level schematic — not verified wiringdirectshands off tohands off todelivers toHuman operatorHumanoperatorHUMANGATEStage 1 agentStage 1 agentBUILDERStage 2 agentStage 2 agentBUILDERQA reviewerQA reviewerQAOutput artifactOutputartifactRESOURCE
Node details

Typical Pipeline layout — schematic, not verified wiring

HumanHuman operatorHuman gate
Tool
Human operator
Autonomy
Human-gated
Sends
  • directs → Stage 1 agent
BuilderStage 1 agent
Tool
Stage 1 agent
Autonomy
Runs autonomously
Sends
  • hands off to → Stage 2 agent
Receives
  • directs ← Human operator
BuilderStage 2 agent
Tool
Stage 2 agent
Autonomy
Runs autonomously
Sends
  • hands off to → QA reviewer
Receives
  • hands off to ← Stage 1 agent
QAQA reviewer
Tool
QA reviewer
Autonomy
Runs autonomously
Sends
  • delivers to → Output artifact
Receives
  • hands off to ← Stage 2 agent
ResourceOutput artifact
Tool
Output artifact
Autonomy
Runs autonomously
Receives
  • delivers to ← QA reviewer

How a typical Pipeline team handles a task

Typical Pipeline layout — schematic, not verified wiring

  1. Task arrives

    Human operator directs Stage 1 agent.

  2. The builders execute

    Stage 1 agent and Stage 2 agent build the work.

  3. Independent review gates the work

    QA reviewer reviews the work. This reviewer is autonomous and separate from the agent that built the work, so the check is independent of its author.

  4. The artifact lands

    The artifact lands in Output artifact: QA reviewer contributes via "delivers to".

  5. Human holds the last word

    Human operator holds final approval.

Replicate a typical Pipeline setup

Typical Pipeline layout — schematic, not verified wiring

Ingredients

  • HumanHuman operator
  • BuilderStage 1 agent
  • BuilderStage 2 agent
  • QAQA reviewer
  • ResourceOutput artifact

Setup order

  1. 1.Provision the substrate: Output artifact.
  2. 2.Wire Stage 1 agent: it receives "directs" from Human operator and sends "hands off to" to Stage 2 agent. Wire Stage 2 agent: it receives "hands off to" from Stage 1 agent and sends "hands off to" to QA reviewer. Wire QA reviewer: it receives "hands off to" from Stage 2 agent.
  3. 3.Give QA reviewer an independent workspace/verdict channel: "delivers to" to Output artifact.
  4. 4.Declare the human gate: Human operator holds final approval.
🔍
CrewAI ResearcherResearcher

CrewAI

[unknown]

📈
CrewAI AnalystAnalyst

CrewAI

[unknown]

Performance metrics

Windowed metrics with provenance. [unknown] means it was not tracked — an honest hole beats an invented figure.

Task success ratenot estimated
[unknown]
evidence-linkedwhy?

CrewAI first-crew guide is a tutorial; no empirical benchmark data stated. Source: docs.crewai.com/guides/crews/first-crew

as of Jan 1, 2024

Token economics

Cost transparency is part of the honesty architecture. [unknown] means it was not tracked — not that it is zero.

No cost metrics on record. Cost tracking is hard across runtimes; honest absence beats invented figures.

Blueprint

Operational DNA — why it works, how it was built, and how it is overseen. Not files for sale; knowledge of the design.

Why it works

Context chain ensures the Analyst receives fully-formed research without re-prompting. Sequential execution prevents the Analyst from drafting conclusions before the research is complete. State persistence via Flows allows multi-step pipelines to survive interruptions.

How it was built

CrewAI framework. Agents defined with specialized goals and tools. Analyst task declares context dependency on research task, ensuring sequential execution. Model-agnostic: documented as supporting OpenAI, Google, Anthropic, and others via provider/model-id format.

Oversight model

Event-driven execution with state persistence: "Persist data across steps and executions." Flows manage the state and re-routing decisions.

Proof (1)

The team's shared track record — tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.

  1. ArtifactJan 1, 2024evidence-linked

    CrewAI sequential crew pattern documented in official docs

    Researcher + Analyst sequential pipeline with context chain. Supports multiple LLM providers. Flows enable state-managed, event-driven higher-level orchestration.

    https://docs.crewai.com/en/guides/crews/first-crew

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Attestations (0)

Named third-party statements from people with first-hand experience. Attestations are what separates Peer-Attested from Evidence-Linked.

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