crewai
Design Reliable CrewAI Agent Teams
Multi-agent projects often fail because roles, tasks, dependencies, and control flow are unclear. This skill provides practical CrewAI patterns for structured Python workflows.
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Install with my Agent
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Review the Skillstore skill "crewai" from https://skillstore.io/skills/sickn33-crewai.md and its manifest at https://skillstore.io/api/skills/sickn33-crewai/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "crewai". Design a crew that researches a market and produces an executive brief.
Expected outcome:
- Research agent: gathers cited market evidence from approved sources.
- Analyst agent: compares trends, competitors, and uncertainties.
- Writer agent: produces the brief from reviewed research and analysis.
- Process: sequential, with explicit expected outputs and a review gate.
Using "crewai". Should a support-triage crew use sequential or hierarchical execution?
Expected outcome:
Use hierarchical execution when a manager must assign cases by specialty and resolve conflicts. Use sequential execution for a fixed classify, investigate, and respond pipeline.
Using "crewai". Review a CrewAI workflow that gives every agent every tool.
Expected outcome:
- Primary risk: excessive tool access increases the effect of mistakes and prompt injection.
- Recommendation: assign only task-specific tools and require approval for sensitive actions.
- Validation: test denied operations, malformed inputs, timeouts, and partial failures.
Security Audit
High RiskAll seven static command findings are false positives caused by Markdown fences or inline code, with no Ruby or shell execution present. Semantic review identified unrestricted agent-controlled SQL execution and untrusted web research flowing into a downstream agent. Add database controls and indirect prompt injection defenses before publication.
Confirmed security concerns (2)
Risk Factors
⚙️ External commands (7)
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APA citation
sickn33. (2026). crewai security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-crewai/audits/5BibTeX citation
@techreport{sickn33-sickn33-crewai-2026,
author = {sickn33},
title = {crewai security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-crewai/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "crewai security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-crewai/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-crewai:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
Build a Research and Writing Crew
Design agents, tasks, and context dependencies for a repeatable research-to-content workflow.
Choose an Orchestration Process
Compare sequential and hierarchical processes for a multi-agent workload with clear delegation needs.
Plan a Stateful Agent Workflow
Map events, routers, memory, and specialized crews into a controlled CrewAI Flow.
Try These Prompts
Design a minimal CrewAI team for [goal]. Define each agent, task, expected output, and execution order. Explain the choices.
Convert this workflow into CrewAI agent and task configuration: [workflow]. Include roles, goals, dependencies, inputs, and expected outputs.
Assess this multi-agent workflow: [details]. Recommend sequential or hierarchical execution. Identify delegation boundaries, dependencies, and failure points.
Design a CrewAI Flow for [system]. Include state, routing, memory, approval gates, tool permissions, error handling, observability, and test criteria.
Best Practices
- Give every agent one clear responsibility and measurable expected outputs.
- Use least-privilege tools, validated inputs, and approval gates for sensitive actions.
- Test task dependencies, routing, memory behavior, retries, and partial failures.
Avoid
- Do not create many agents when a deterministic function or single model call is sufficient.
- Do not pass untrusted retrieved content into agent instructions without isolation and validation.
- Do not expose unrestricted database, filesystem, or network tools to autonomous agents.