ai-agent-development
Build Reliable AI Agent Systems
AI agent projects often lack a structured path from architecture through evaluation. This workflow organizes design, implementation, orchestration, tools, memory, and testing into seven phases.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "ai-agent-development" from https://skillstore.io/skills/sickn33-ai-agent-development.md and its manifest at https://skillstore.io/api/skills/sickn33-ai-agent-development/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.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 "ai-agent-development". Design a support agent that summarizes tickets and drafts replies.
Expected outcome:
- Purpose: reduce response preparation time while keeping final approval with support staff.
- Tools: ticket reader, knowledge search, draft writer, and escalation handler.
- Memory: current ticket context and approved customer preferences.
- Quality gates: citation accuracy, policy compliance, appropriate escalation, and human approval.
Using "ai-agent-development". Plan a CrewAI workflow for reviewing software releases.
Expected outcome:
- Release analyst checks scope, dependencies, and change records.
- Test reviewer evaluates coverage, failures, and unresolved risks.
- Security reviewer checks sensitive changes and required approvals.
- Coordinator consolidates findings and blocks release when mandatory gates fail.
Using "ai-agent-development". Outline a LangGraph workflow for a research assistant.
Expected outcome:
The workflow routes requests through planning, source collection, evidence review, synthesis, citation checks, and human approval before completion.
Security Audit
SafeAll 32 static findings are false positives caused by Markdown backticks around skill names and fenced text examples in SKILL.md. The file contains workflow guidance only, with no executable Ruby, shell commands, prompt injection, or other semantic security concern.
Risk Factors
⚙️ External commands (32)
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<iframe src="https://skillstore.io/embed/skills/sickn33-ai-agent-development.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). ai-agent-development security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-ai-agent-development/audits/5BibTeX citation
@techreport{sickn33-sickn33-ai-agent-development-2026,
author = {sickn33},
title = {ai-agent-development security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-ai-agent-development/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: "ai-agent-development security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-ai-agent-development/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-ai-agent-development:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Plan a First Autonomous Agent
Turn a product goal into defined capabilities, tools, memory, safety boundaries, and success metrics.
Coordinate a Multi-Agent Team
Define specialized roles, communication paths, delegation rules, and coordination tests for a CrewAI system.
Build Stateful Agent Workflows
Plan LangGraph states, conditional branches, persistence, tool interfaces, memory, and evaluation scenarios.
Try These Prompts
Design a single AI agent for [goal]. Define its users, inputs, outputs, capabilities, tools, memory, safety boundaries, and success metrics.
Design a CrewAI system for [workflow]. Specify each role, responsibilities, shared context, delegation rules, communication paths, failure handling, and coordination tests.
Create a LangGraph workflow for [process]. Define state, nodes, transitions, conditional branches, checkpoints, retries, human approvals, persistence, and termination criteria.
Evaluate [agent system] against [goals]. Create representative scenarios, edge cases, tool failures, safety tests, measurable criteria, and an improvement plan.
Best Practices
- Define permissions, success metrics, and stop conditions before selecting tools or frameworks.
- Test tool failures, ambiguous inputs, unsafe requests, and human escalation paths.
- Evaluate each agent independently before testing coordination and end-to-end behavior.
Avoid
- Do not grant broad tool access without explicit permissions and validation.
- Do not add multiple agents when one agent and a deterministic workflow are sufficient.
- Do not rely on conversational memory for durable state or auditable records.
Frequently Asked Questions
Does this skill generate complete agent code?
Which agent frameworks does it cover?
Can I use it for a single agent?
Does it include human approval patterns?
What inputs should I prepare?
How should I validate the final agent system?
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/ai-agent-developmentRef
ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006
Maintenance freshness
7/26/2026
Usage
6 downloads · 108 views
File structure
📄 SKILL.md