076-Frank-智能体设计工具

076-Frank-智能体设计工具 is a skill for Claude Code, Codex from frank666199/frank-presales-skills. It costs 0 tokens per session (605 once invoked), scanned A, original, MIT.

A design guide for an AI agent: a software system that understands tasks, makes plans, uses tools, remembers relevant information, and returns results.

In plain words
What is it for?
Use it to document agent architecture, API and database integrations, file or code operations, task flows, error handling, and performance requirements.
Why use it?
It makes the agent’s responsibilities, tool access, workflow, memory, safety boundaries, and fallback behavior explicit before implementation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to document agent architecture, API and database integrations, file or code operations, task flows, error handling, and performance requirements.

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Install with agentmods
npx agentmods add skills/frank666199/frank-presales-skills/076-frank
Install

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.

Any agent
npx skills add frank666199/frank-presales-skills --skill 076-frank
Clone the repo
git clone --depth 1 https://github.com/frank666199/frank-presales-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for 076-Frank-智能体设计工具

README.md
[![agentmods](https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/076-frank/github.svg)](https://agentmods.dev/skills/frank666199/frank-presales-skills/076-frank)
Your own site
<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/076-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/076-frank/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.

agentmods 80×15 button for 076-Frank-智能体设计工具

Your own site · 80×15
<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/076-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/076-frank.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 605 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00605
Opus 5 $0.00000 $0.00302
Sonnet 5 $0.00000 $0.00121
Haiku 4.5 $0.00000 $0.00060

Measured 9d ago against content hash b28564dc0cd1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

076-Frank-智能体设计工具 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 9d 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.

维度7-AI-Projects/076-Frank-智能体设计工具/SKILL.md · 89 lines

What it actually says

Skill: Frank-智能体设计工具

Profile

  • Author: Frank
  • Version: 1.0.0
  • Language: 中文
  • Category: 维度7 - AI项目专精
  • Description: 设计AI Agent架构,生成智能体工作流

When to Use

AI项目中需要设计Agent方案


Input Requirements

  • 业务场景
  • 任务流程
  • 可用工具/API

Workflow

  1. 设计Agent架构:感知模块→规划模块→记忆模块→工具模块→行动模块
  2. 定义Agent角色和能力边界
  3. 设计工作流:任务理解→计划制定→工具调用→结果整合→输出反馈
  4. 规划记忆系统:短期记忆(对话上下文)+长期记忆(向量数据库)
  5. 设计工具集成:API调用/数据库查询/文件操作/代码执行
  6. 制定异常处理和回退策略
  7. 输出Agent设计文档

Output Format

Agent设计文档(含架构图+工作流+记忆设计+工具集成+异常处理)


Output Template

Agent模块 | 功能 | 技术实现 | 工具/依赖 | 异常处理 | 性能指标

Example

字段 内容
规划模块 任务分解和计划制定

Constraints

  • Agent能力边界明确
  • 工具调用安全可控
  • 异常处理完善

Quality Criteria

  • 架构设计合理
  • 工作流覆盖完整
  • 安全边界清晰

Applicable Scenarios

  • G端政府项目: 部分适用
  • B端企业项目: 部分适用
  • AI智能项目: 适用

Usage

方式1:Claude Code / Cursor / Codex

将本SKILL.md内容复制到Agent技能配置区,通过技能名触发。

方式2:飞书妙搭 / 扣子

将SKILL.md内容粘贴到Agent提示词配置区,设置触发词为技能名。

方式3:独立使用

直接复制本文件内容到AI对话中,按Workflow步骤执行。


Frank专属售前技能 | 维度7: AI项目专精 | 编号: 076 基于"Frank售前解决方案Skills工具集 v1.0"与实操提示词融合优化生成

Changes

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.

  1. 9d ago First seen · 89 lines · 0 tokens per session scan A b28564dc0cd1

Subscribe to this mod's changes

076-Frank-智能体设计工具 is a skill published in the GitHub repository frank666199/frank-presales-skills (11 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 605 tokens. 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 2026-09-03.

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