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codenova58

Agent Arch

by codenova58 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
120
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0
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0
Active Installs
1
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Install in OpenClaw
/install agent-arch
Description
Agent loops, memory, tools, and safety boundaries. Use when designing AI agents.
README (SKILL.md)

Agent Architecture Skill

This skill provides structured guidance for Agent Architecture work. Act as an active guide: confirm triggers, propose the stages below, and adapt if the user wants a lighter pass.

When to Offer This Workflow

Trigger conditions:

  • User mentions agent architecture or closely related work
  • They want a structured workflow rather than ad-hoc tips
  • They are preparing a review, rollout, or stakeholder communication

Initial offer: Explain the four stages briefly and ask whether to follow this workflow or work freeform. If they decline, continue in their preferred style.

Workflow Stages

Stage 1: Clarify context & goals

Anchor on goals, tools, and constraints. Ask what success looks like, constraints, and what must not break. Capture unknowns early.

Stage 2: Design or plan the approach

Translate goals into a concrete plan around memory and state. Compare alternatives and explicit trade-offs; avoid implicit assumptions.

Stage 3: Implement, validate, and harden

Execute with verification loops tied to planning loops and stopping. Prefer small steps, measurable checks, and rollback points where risk is high.

Stage 4: Operate, communicate, and iterate

Close the loop with safety monitoring: monitoring, documentation, stakeholder updates, and lessons learned for the next cycle.

Checklist Before Completion

  • Goals and constraints are explicit for Agent Architecture Skill
  • Risks and trade-offs are stated, not hand-waved
  • Verification steps match the change’s impact (tests, canary, peer review)
  • Operational follow-through is covered (monitoring, docs, owners)

Tips for Effective Guidance

  • Be procedural: stage-by-stage, with clear exit criteria
  • Ask for missing context (environment, scale, deadlines) before prescribing
  • Prefer checklists and concrete examples over generic platitudes
  • If the user declines the workflow, switch to freeform help without lecturing

Handling Deviations

  • If the user wants to skip a stage: confirm and continue with what they need.
  • If context is missing: ask targeted questions before strong recommendations.
  • Prefer concrete examples, trade-offs, and verification steps over generic advice.

Quality Bar

  • Each recommendation should be actionable (what to do next).
  • Call out failure modes relevant to Agent Architecture (security, scale, UX, or ops).
  • Keep tone direct and respectful of the user’s time.
Usage Guidance
This skill is an advice/workflow template only and appears safe and coherent to install. Before enabling or trusting any agent to act autonomously with it, skim the SKILL.md so you understand the questions the skill will ask and the kind of project details it may request. Do not provide secrets, credentials, or access to systems in conversation unless you explicitly intend to do so. If a future version adds install steps, external URLs, file reads, or requests for API keys, treat that as a material change and re-evaluate.
Capability Analysis
Type: OpenClaw Skill Name: agent-arch Version: 1.0.0 The skill bundle contains only metadata and a markdown file (SKILL.md) providing structured guidance for designing AI agent architectures. It lacks any executable code, network requests, or malicious instructions, focusing instead on a four-stage workflow for planning, implementation, and safety monitoring.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md content: the skill is a structured workflow for agent architecture and does not request unrelated credentials, binaries, or config paths.
Instruction Scope
Runtime instructions are purely procedural guidance (ask questions, propose stages, checklists). They do not instruct reading files, accessing environment variables, calling external endpoints, or executing binaries.
Install Mechanism
No install spec and no code files — instruction-only skills write nothing to disk and have minimal surface area.
Credentials
The skill declares no environment variables, credentials, or config paths; the guidance requests only conversational context from the user, which is appropriate for its purpose.
Persistence & Privilege
always is false and the skill is user-invocable; it does not request elevated or persistent privileges beyond normal autonomous invocation behavior.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-arch
  3. After installation, invoke the skill by name or use /agent-arch
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the Agent Architecture Skill. - Provides a structured 4-stage workflow for agent architecture: clarify context & goals, design or plan approach, implement/validate, and operate/iterate. - Includes trigger conditions for when to propose the workflow. - Offers a checklist for thoroughness before marking work complete. - Emphasizes step-by-step guidance, risk transparency, and verification steps. - Adapts to user preferences (structured or freeform). - Supplies tips and quality standards focused on actionable advice and concrete examples.
Metadata
Slug agent-arch
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Agent Arch?

Agent loops, memory, tools, and safety boundaries. Use when designing AI agents. It is an AI Agent Skill for Claude Code / OpenClaw, with 120 downloads so far.

How do I install Agent Arch?

Run "/install agent-arch" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Arch free?

Yes, Agent Arch is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Agent Arch support?

Agent Arch is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Arch?

It is built and maintained by codenova58 (@codenova58); the current version is v1.0.0.

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