AI Team crewai Analytics Untested multi-agent free

Data Analysis — CrewAI

Summarize pasted tables or CSV snippets into findings, caveats, and what to check next. Analysis only. (CrewAI multi-agent Python sketch for one job.)

Id: crewai/data-analysis · Slug: data-analysis · Status: Untested · Untested on this machine — recipe reviewed for safety (no secrets, no destructive commands, no auto-spend). Mark tested after you run it locally.

What is this

AI Team for CrewAI. Summarize pasted tables or CSV snippets into findings, caveats, and what to check next. Analysis only. (CrewAI multi-agent Python sketch for one job.)

How this runtime fits

This CrewAI sketch is a AI Team implementation typed as AI Team in the catalog. Where roles coordinate, it is fair to call it an agent team or multi-agent system — not a swarm.

Parent AI Team: data-analysis · What is an AI Team?

What it does

Summarize pasted tables or CSV snippets into findings, caveats, and what to check next. Analysis only. (CrewAI multi-agent Python sketch for one job.)

Who for

Builders working on Analytics jobs who can run CrewAI themselves.

Works with

Need to run

You will run this locally or on infra you control.
No production credentials in prompts or committed files.
Python 3.10+
CrewAI in a venv
Local or keyed LLM endpoint with budget awareness

How to use

Create a venv; install CrewAI (pin versions yourself).
Configure a local OpenAI-compatible base URL when possible.
Save crew_data_analysis.py and run: python crew_data_analysis.py
Replace PASTE_EXAMPLE_IN with your real input.
Read Pass/Fail gate output before trusting the draft.

Limitations

Not a substitute for professional legal, medical, or investment advice.
Outputs can be wrong; human review required before publish or spend.
Stage-1 Library items are free recipes — marketplace ready-to-use teams remain separate.
Do not attach billing cloud LLM nodes without a human budget check.

Test status

Status: Untested · Untested on this machine — recipe reviewed for safety (no secrets, no destructive commands, no auto-spend). Mark tested after you run it locally.

Files

crew_data_analysis.py — CrewAI agents + tasks
requirements-hint.txt — Suggested packages (pin yourself)

Full prompt / config / code

# crew_data_analysis.py — Data Analysis (CrewAI)
# Safety: local/OpenAI-compatible endpoint preferred. No keys in source.
# pip install crewai  (pin versions yourself)

from crewai import Agent, Task, Crew, Process

SYSTEM = """You are a data analysis desk. Goal: findings from pasted numbers only.

RULES:
- Do not invent rows. If math is approximate, say so.
- Call out sample size, missing fields, and selection bias.
- No trading/investment advice. No auto-spend recommendations.
- Charts described in text only unless user provides image.

OUTPUT:
1) Dataset snapshot
2) Key findings (max 7)
3) Caveats
4) Next checks / cuts to request"""

GOAL = "Summarize pasted tables or CSV snippets into findings, caveats, and what to check next. Analysis only."

lead = Agent(
    role="Data Analysis lead",
    goal=GOAL,
    backstory="Local BotShelf operator. One job, then stop. No spend. No destructive tools.",
    allow_delegation=False,
    verbose=False,
)

reviewer = Agent(
    role="Quality gate",
    goal="Check the lead output against the required sections; list gaps only.",
    backstory="Pedantic reviewer. Does not invent facts.",
    allow_delegation=False,
    verbose=False,
)

produce = Task(
    description=(
        "Follow SYSTEM strictly.\n\nSYSTEM:\n" + SYSTEM +
        "\n\nUSER INPUT:\n{user_input}"
    ),
    expected_output="Complete Data Analysis structured result.",
    agent=lead,
)

gate = Task(
    description=(
        "Verify the previous result has all required sections. "
        "Return Pass/Fail + missing sections. Do not rewrite creatively."
    ),
    expected_output="Pass/Fail and gap list.",
    agent=reviewer,
)

crew = Crew(
    agents=[lead, reviewer],
    tasks=[produce, gate],
    process=Process.sequential,
)

def run(user_input: str) -> str:
    return str(crew.kickoff(inputs={"user_input": user_input}))

if __name__ == "__main__":
    print(run("PASTE_EXAMPLE_IN"))

Example in

Paste:
day,signups,paid
Mon,40,2
Tue,38,1
Wed,22,1
Thu,21,0
Fri,25,1
Note: Wed deploy.

Example out

Snapshot: 5 weekdays; Wed deploy coincides with signup drop.
Findings: Signups fell ~45% Wed–Thu vs Mon–Tue; paid sparse (n small).
Caveats: one week; no traffic denominator.
Next: traffic + error logs around deploy.

Model / runtime notes

Two-agent crew (produce + gate). Keep tools disabled unless you add read-only tools on purpose.

Canonical Team

Parent: data-analysis · implementation_id: crewai/data-analysis

GitHub source

teams/data-analysis/crewai · commit eb87e8e049fdf9908e438305ff827c7b617505b5 · license: free-use-at-own-risk

Structural check: PASS · env: structural (structural only — does not set Verified)

Related Library items

Related marketplace Team pages

Soft thematic links only — not identity merges. Marketplace Teams ≠ Library AI Team records.

Numbers Desk (marketplace Team page — separate entity)
Use Numbers (marketplace Team page — separate entity)