Skills ai-agents-architect
📦

ai-agents-architect

Content revision r2 Safe ⚙️ External commands

Design Reliable Autonomous AI Agents

Autonomous agent projects often fail through weak controls, unclear tools, and unsuitable architecture. This skill guides practical designs for planning, memory, recovery, orchestration, and observability.

Supports: Claude Codex Code(CC)
🥉 77 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-agents-architect" from https://skillstore.io/skills/sickn33-ai-agents-architect.md and its manifest at https://skillstore.io/api/skills/sickn33-ai-agents-architect/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-agents-architect.md Signed manifest GET /api/skills/sickn33-ai-agents-architect/manifest Signed lockfile GET /api/skills/sickn33-ai-agents-architect/lockfile

Test it

Using "ai-agents-architect". Design a support agent that searches documentation and drafts answers.

Expected outcome:

  • Pattern: ReAct with a maximum of six tool iterations.
  • Tools: documentation search, article retrieval, and answer submission.
  • Controls: citation requirements, timeout handling, and human review for uncertain answers.

Using "ai-agents-architect". Plan recovery for a research agent that may run for several hours.

Expected outcome:

  • Checkpoint after each completed research section.
  • Store task progress separately from retrieved source summaries.
  • Resume from the latest valid checkpoint and clear temporary data after completion.

Using "ai-agents-architect". Decide whether a content workflow needs multiple agents.

Expected outcome:

Start with one agent using focused research, drafting, and review tools. Add specialists only when measured failures show that role separation improves results.

Security Audit

Safe
v5 • 7/23/2026 Open versioned report

Both static findings are false positives caused by ordinary prose and inline Markdown identifiers. The skill contains architectural guidance without executable commands, network reconnaissance, or semantic threats.

1
Files scanned
341
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

⚙️ External commands (1)
SKILL.md:321
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-agents-architect security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-ai-agents-architect/audits/5

BibTeX citation

@techreport{sickn33-sickn33-ai-agents-architect-2026, author = {sickn33}, title = {ai-agents-architect security audit report (audit version 5)}, institution = {Skillstore}, year = {2026}, number = {5}, url = {https://skillstore.io/skills/sickn33-ai-agents-architect/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-agents-architect 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-agents-architect/audits/5" identifiers: - type: other value: "skillstore:sickn33-ai-agents-architect:audit:5" description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: High
55
Architecture
85
Maintainability
87
Content
67
Community
83
Spec Compliance

What You Can Build

Design a First Tool-Using Agent

Choose an agent loop, define focused tools, and add practical limits for a bounded application workflow.

Plan a Long-Running Agent Platform

Structure memory, checkpoints, recovery, and observability for agents that maintain task progress across failures.

Review Agent Reliability

Identify uncontrolled loops, silent tool errors, excessive memory, brittle parsing, and unnecessary multi-agent complexity.

Try These Prompts

Choose an Agent Pattern 
Design an AI agent for [task]. Compare ReAct and plan-and-execute, then recommend one with required tools, limits, and failure conditions.
Specify Tools and Controls 
Create a tool plan for an agent that handles [workflow]. Define each tool purpose, parameters, errors, retries, permissions, and execution limits.
Design Memory and Recovery 
Architect memory and checkpoint recovery for [long-running task]. Separate working, episodic, and semantic memory, with retention, retrieval, cleanup, and resumption rules.
Evaluate a Multi-Agent System 
Review this proposed multi-agent system: [architecture]. Assess role boundaries, handoffs, supervisor logic, failure recovery, observability, cost, and whether one agent is sufficient.

Best Practices

  • Set iteration, token, time, and cost limits before enabling autonomous execution.
  • Give every tool a clear purpose, typed parameters, examples, permissions, and recoverable error responses.
  • Trace decisions, tool calls, latency, token usage, checkpoints, and final outcomes.

Avoid

  • Do not run agent loops without explicit stopping conditions and circuit breakers.
  • Do not store every observation or expose large tool catalogs without relevance filtering.
  • Do not introduce multiple agents before one well-equipped agent demonstrates measurable limitations.

Frequently Asked Questions

Which agent patterns does this skill cover?
It covers ReAct, plan-and-execute, tool registries, hierarchical memory, supervisor coordination, and checkpoint recovery.
Does this skill generate runnable code?
It focuses on architecture and design guidance. Implementation still depends on your language, framework, models, and infrastructure.
Can it help define agent tools?
Yes. It guides tool purpose, selection, parameter documentation, examples, error handling, retries, and focused tool sets.
How does it address runaway costs?
It recommends iteration limits, token limits, timeouts, cost caps, and circuit breakers for repeated tool failures.
When should I use multiple agents?
Use them when independent specialist roles provide measured benefits that justify coordination, debugging, latency, and cost overhead.
Does it cover production monitoring?
It recommends structured tracing for actions, tool inputs, outputs, errors, token usage, latency, and recovery events.

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-agents-architect

Ref

ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006

Maintenance freshness

7/26/2026

Usage

7 downloads · 32 views

File structure

📄 SKILL.md