AI Team crewai Sales Untested multi-agent free

Lead Research — CrewAI

Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (CrewAI multi-agent Python sketch for one job.)

Id: crewai/lead-research · Slug: lead-research · 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. Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (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: lead-research · What is an AI Team?

What it does

Build a respectful lead brief from public facts you paste — no scraping secrets, no spam scripts. (CrewAI multi-agent Python sketch for one job.)

Who for

Builders working on Sales 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_lead_research.py and run: python crew_lead_research.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.
No harvesting of personal data beyond what the operator pasted.

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

Full prompt / config / code

# crew_lead_research.py — Lead Research (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 respectful lead-research desk. Goal: brief from public facts the user pasted.

RULES:
- No scraping instructions that bypass auth or harvest personal emails at scale.
- No spam sequences. Suggest one human-sent outreach angle max.
- Separate public fact vs guess.
- Do not store or request secrets.

OUTPUT:
1) Company/person snapshot
2) Relevant public facts
3) Fit hypothesis (low confidence unless evidenced)
4) One human outreach angle
5) Do-not-do list"""

GOAL = "Build a respectful lead brief from public facts you paste \u2014 no scraping secrets, no spam scripts."

lead = Agent(
    role="Lead Research 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 Lead Research 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

Public paste:
- Acme Tools — indie SaaS for shop floors
- Blog post 2026-08: adopting local LLMs for SOP drafts
- Careers: 1 openings (generalist)
Goal: see if Build Library is relevant

Example out

Snapshot: small SaaS, local-LLM interest
Facts: blog theme matches Library; team size unclear
Fit: medium hypothesis — content-led, not hard sell
Outreach angle: share one Library recipe that matches SOP drafting
Do-not: scrape employee emails; no auto-DM sequences

Model / runtime notes

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

Canonical Team

Parent: lead-research · implementation_id: crewai/lead-research

GitHub source

teams/lead-research/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.

Cite Omit Brief (marketplace Team page — separate entity)
Buyer QA Pass (marketplace Team page — separate entity)