Skills ai-agent-development
📦

ai-agent-development

Content revision r2 Safe ⚙️ External commands

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.

Supports: Claude Codex Code(CC)
🥉 78 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
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.

Markdown detail GET /skills/sickn33-ai-agent-development.md Signed manifest GET /api/skills/sickn33-ai-agent-development/manifest Signed lockfile GET /api/skills/sickn33-ai-agent-development/lockfile

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

Safe
v5 • 7/23/2026 Open versioned report

All 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.

1
Files scanned
179
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

⚙️ External commands (32)
SKILL.md:30 SKILL.md:31 SKILL.md:41-43 SKILL.md:43-48 SKILL.md:48-49 SKILL.md:49-59 SKILL.md:59-61 SKILL.md:61-66 SKILL.md:66-67 SKILL.md:67-77 SKILL.md:77-79 SKILL.md:79-84 SKILL.md:84-85 SKILL.md:85-95 SKILL.md:95-97 SKILL.md:97-102 SKILL.md:102-103 SKILL.md:103-113 SKILL.md:113-115 SKILL.md:115-120 SKILL.md:120-121 SKILL.md:121-131 SKILL.md:131-133 SKILL.md:133-138 SKILL.md:138-139 SKILL.md:139-149 SKILL.md:149-151 SKILL.md:151-155 SKILL.md:155-159 SKILL.md:159-171 SKILL.md:171-172 SKILL.md:172-173
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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Open versioned report
Security Assessment

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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/5

BibTeX 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: High
55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance

What 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 Agent 
Design a single AI agent for [goal]. Define its users, inputs, outputs, capabilities, tools, memory, safety boundaries, and success metrics.
Assign Multi-Agent Roles 
Design a CrewAI system for [workflow]. Specify each role, responsibilities, shared context, delegation rules, communication paths, failure handling, and coordination tests.
Orchestrate with LangGraph 
Create a LangGraph workflow for [process]. Define state, nodes, transitions, conditional branches, checkpoints, retries, human approvals, persistence, and termination criteria.
Evaluate and Harden an Agent 
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?
No. It provides a phased workflow and prompts that guide architecture, implementation, integration, and evaluation.
Which agent frameworks does it cover?
It references CrewAI for multi-agent systems and LangGraph for stateful orchestration, while supporting custom agent designs.
Can I use it for a single agent?
Yes. The workflow includes dedicated phases for single-agent design, implementation, tools, memory, and evaluation.
Does it include human approval patterns?
Yes. Human-in-the-loop design is within scope, but each implementation must define its own approval points and permissions.
What inputs should I prepare?
Provide the goal, target users, available tools, data boundaries, required permissions, safety constraints, and measurable success criteria.
How should I validate the final agent system?
Test normal tasks, edge cases, tool failures, unsafe requests, memory behavior, orchestration, escalation, and measurable quality criteria.

Developer Details

Author

sickn33

License

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-development

Ref

ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006

Maintenance freshness

7/26/2026

Usage

6 downloads · 108 views

File structure

📄 SKILL.md

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