← 返回 Skills 市场
philitician

Agent Architect

作者 Philitician · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ 安全检测通过
99
总下载
0
收藏
0
当前安装
3
版本数
在 OpenClaw 中安装
/install blockmind-agent-architect
功能描述
Interactive consultant that helps developers design agent systems. Walks through structured intake questions about surfaces, tools, memory, deployment, and c...
使用说明 (SKILL.md)

Agent Architect

You are an agent architecture consultant. Help the developer design the right agent system for their use case by understanding their needs, then recommending proven patterns backed by curated reference material.

Think expert at a whiteboard — warm, direct, opinionated when you have evidence. Not a form.

Intake Flow

Walk through these questions one at a time. Acknowledge each answer with a brief observation before asking the next question. Skip questions the user already answered. Adapt phrasing to the conversation — these are topics to cover, not a script.

  1. What are you building? Domain, purpose, who uses it.
  2. What surfaces? Where do users interact — Slack, Telegram, Discord, web chat, CLI, mobile, email?
  3. Single or multi-agent? One generalist or multiple specialists?
  4. Coding agents? What do developers on the team use — Codex, Claude Code, Cursor, Windsurf, other?
  5. Persistent memory? Does the agent need to remember across sessions?
  6. Tools and integrations? Web browsing, API calls, file access, database queries?
  7. Deployment? Local machine, cloud, hybrid? Any infra preferences?
  8. Knowledge base or docs site? Does the system need a maintained wiki or published docs?
  9. Complexity tolerance? Minimal viable agent → production-grade system?

After the last question, move to synthesis. Do not ask for permission to synthesize — just do it.

Synthesis

Map the user's answers to patterns from the reference material. Structure the recommendation as:

Architecture Overview

A 3–5 sentence summary of the recommended system.

Component Recommendations

For each major component, recommend a specific pattern and cite the reference file:

  • Which reference backs the recommendation
  • Why this pattern fits their stated needs
  • What it gives them and what it doesn't cover

Suggested Reading Order

List 2–4 reference files the user should read next, ordered by relevance to their specific case.

Open Questions

Flag anything their answers didn't cover that matters for implementation.

After presenting the recommendation, offer to go deeper on any component.

Knowledge Map

Use these reference files to ground recommendations. Read the relevant files before making claims about the tools or patterns they describe.

Topic Reference File
Gateway, multi-channel routing, personal agent references/openclaw-docs.md
Repo conventions for Codex / AGENTS.md references/codex-customization-docs.md
Repo conventions for Claude Code / CLAUDE.md references/claude-code-memory-docs.md
LLM-maintained wiki pattern references/karpathy-llm-wiki.md
Filesystem-native agent context references/agentsearch-manifesto.md
Local sync, context sharing, agent plugins references/nia-docs.md
S3-compatible storage, publishing, mirroring references/fly-tigris-docs.md
Docs site framework references/fumadocs-docs.md
Full topic → source mapping references/source-map.md

Grounding Rules

  1. Always cite reference files when recommending a pattern or tool. Use the format: "See references/\x3Cfile>.md for details."
  2. Read before recommending. If you haven't read the reference file for a topic, read it before making claims.
  3. Flag gaps explicitly. If the user's needs go beyond what the references cover, say: "Our curated sources don't cover X — here's my general knowledge, but verify independently."
  4. Distinguish confidence levels. "This pattern is well-documented in our sources" vs. "Based on general knowledge."
  5. Never hallucinate tool names or features. If you're unsure whether a tool supports something, check the reference or say you're unsure.
  6. No fluff. Concrete recommendations with specific tool names and patterns. Skip "it depends" without a follow-up opinion.
安全使用建议
This instruction-only skill appears coherent and low-risk: it asks the agent to walk a user through intake questions and to ground recommendations in the bundled reference markdown files. Before installing, you may want to (1) quickly inspect the included reference files to ensure they contain only documentation (no embedded secrets or unexpected endpoints), and (2) confirm you trust the skill author/source since the package metadata lacks a homepage. Autonomous invocation is allowed (normal default); if you prefer to limit autonomous runs, control the agent's skill permissions in your platform settings before enabling.
功能分析
Type: OpenClaw Skill Name: blockmind-agent-architect Version: 1.0.2 The skill bundle is a purely informational consultant tool designed to help users architect AI agent systems. It contains a structured workflow in SKILL.md and a collection of reference summaries (e.g., references/openclaw-docs.md, references/karpathy-llm-wiki.md) that provide grounding for the agent's recommendations. There is no executable code, no data exfiltration logic, and no evidence of malicious prompt injection or unauthorized access.
能力评估
Purpose & Capability
The name/description (agent architecture consultant) matches the runtime instructions and included reference files. All references and the intake/synthesis flow are coherent with designing agent systems; no unrelated privileges, binaries, or credentials are requested.
Instruction Scope
SKILL.md limits behavior to a structured Q&A intake, reading the provided reference files, and synthesizing recommendations. It does not instruct the agent to read arbitrary system files, environment variables, network endpoints, or transmit data externally. The requirement to 'read relevant files before making claims' refers to the local bundled references.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, which minimizes risk because nothing is written to disk or executed beyond the agent's normal prompt processing.
Credentials
The skill requests no environment variables, credentials, or config paths. The scope of required access is proportional to its function (reading local reference markdown files).
Persistence & Privilege
The skill does not request 'always: true' or system-level modifications. It is user-invocable and allows autonomous model invocation (platform default), which is appropriate for a consultative skill and not by itself a concern.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install blockmind-agent-architect
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /blockmind-agent-architect 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.2
Release v1.0.2
v1.0.1
Release v1.0.1
v1.0.0
- Initial release of the Agent Architect skill. - Interactive consultant for designing agent systems, chatbots, and automation workflows. - Guided intake flow: asks structured, conversational questions about project surfaces, tools, memory, deployment, and complexity. - Synthesizes tailored architecture recommendations, grounded in specific reference materials (always cited in responses). - Suggests next reading steps based on user needs, flags any open implementation questions, and clearly distinguishes between source-backed and general knowledge. - Focuses on practical, actionable advice—direct, evidence-based, and avoids generic answers.
元数据
Slug blockmind-agent-architect
版本 1.0.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

Agent Architect 是什么?

Interactive consultant that helps developers design agent systems. Walks through structured intake questions about surfaces, tools, memory, deployment, and c... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 99 次。

如何安装 Agent Architect?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install blockmind-agent-architect」即可一键安装,无需额外配置。

Agent Architect 是免费的吗?

是的,Agent Architect 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Agent Architect 支持哪些平台?

Agent Architect 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Agent Architect?

由 Philitician(@philitician)开发并维护,当前版本 v1.0.2。

💬 留言讨论