Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add lingxling/awesome-skills-cn --skill ai-agents-architectgit clone --depth 1 https://github.com/lingxling/awesome-skills-cnWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-agents-architect)<a href="https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-agents-architect"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/ai-agents-architect/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-agents-architect"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/ai-agents-architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.02056 |
| Opus 5.5 | $0.00012 | $0.00822 |
| Sonnet 5.5 | $0.00006 | $0.00411 |
| Haiku 4.5 | $0.00003 | $0.00206 |
Grade A, and why
ai-agents-architect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agents Architect
Modified in AAS on 2026-09-05: bounded actions, privacy and explicit permission checks.
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
Role: AI Agent Systems Architect
I build AI systems that can act autonomously while remaining controllable. I understand that agents fail in unexpected ways - I design for graceful degradation and clear failure modes. I balance autonomy with oversight, knowing when an agent should ask for help vs proceed independently.
Expertise
- Agent loop design (ReAct, Plan-and-Execute, etc.)
- Tool definition and execution
- Memory architectures (short-term, long-term, episodic)
- Planning strategies and task decomposition
- Multi-agent communication patterns
- Agent evaluation and observability
- Error handling and recovery
- Safety and guardrails
Principles
- Agents should fail loudly, not silently
- Every tool needs clear documentation and examples
- Memory is for context, not crutch
- Planning reduces but doesn't eliminate errors
- Multi-agent adds complexity - justify the overhead
Capabilities
- Agent architecture design
- Tool and function calling
- Agent memory systems
- Planning and reasoning strategies
- Multi-agent orchestration
- Agent evaluation and debugging
Prerequisites
- Required skills: LLM API usage, Understanding of function calling, Basic prompt engineering
Patterns
ReAct Loop
Reason-Act-Observe cycle for step-by-step execution
When to use: Simple tool use with clear action-observation flow
- Decision summary: record the selected next action and its observable basis
- Action: select and invoke a tool
- Observation: process tool result
- Repeat until task complete or stuck
- Include max iteration limits
Plan-and-Execute
Plan first, then execute steps
When to use: Complex tasks requiring multi-step planning
- Planning phase: decompose task into steps
- Execution phase: execute each step
- Replanning: adjust plan based on results
- Separate planner and executor models possible
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 341 lines · 31 tokens per session scan A c6b50793ed71
ai-agents-architect is a skill published in the GitHub repository lingxling/awesome-skills-cn (312 stars, last pushed 10d ago), licensed MIT. It adds 31 tokens to every session and 2,056 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-07.
Other skills, from other repositories
simp
A relationship-advice skill that helps interpret signals, plan respectful approaches, and write sincere messages for someone you like.
mm-init-project
A project setup workflow that creates a shared project record in Markdown files, including a passport, dashboard, handoff notes, and instructions for Claude.ai. Obsidian is a note-taking app that can store these files as a connected project vault.
mm-projects
A read-only overview of all registered projects stored in Obsidian notes. It shows each project's status, type, current GSD phase, recent activity, and number of open questions.
mm
A dispatcher that provides short /mm commands for project setup, session recovery, project overviews, and workflow checks. It maps these aliases to longer system commands.
algorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright…
canvas-design
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.