005-Frank-AI竞品分析智能拆解工具

005-Frank-AI竞品分析智能拆解工具 is a skill for Claude Code, Codex from frank666199/frank-presales-skills. It costs 0 tokens per session (620 once invoked), scanned A, original, MIT.

A Chinese-language aid for researching named competitors and comparing them with your own product or proposal across areas such as functions, technology, price, service, and compliance.

In plain words
What is it for?
Use it to prepare competitor matrices, identify defensible differences, and draft sales or proposal strategy recommendations.
Why use it?
It gathers comparison material into one structure and separates confirmed information from items that still need checking.

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 prepare competitor matrices, identify defensible differences, and draft sales or proposal strategy recommendations.

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Install with agentmods
npx agentmods add skills/frank666199/frank-presales-skills/005-frank-ai
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 005-frank-ai
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 005-Frank-AI竞品分析智能拆解工具

README.md
[![agentmods](https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/005-frank-ai/github.svg)](https://agentmods.dev/skills/frank666199/frank-presales-skills/005-frank-ai)
Your own site
<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/005-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/005-frank-ai/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 005-Frank-AI竞品分析智能拆解工具

Your own site · 80×15
<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/005-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/005-frank-ai.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 620 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 $0.00620
Opus 5 $0.00000 $0.00310
Sonnet 5 $0.00000 $0.00124
Haiku 4.5 $0.00000 $0.00062

Measured 12d ago against content hash e91bae446385, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

005-Frank-AI竞品分析智能拆解工具 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 12d 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1-AI-Presales-Tools/005-Frank-AI竞品分析智能拆解工具/SKILL.md · 88 lines

What it actually says

Skill: Frank-AI竞品分析智能拆解工具

Profile

  • Author: Frank
  • Version: 1.0.0
  • Language: 中文
  • Category: 维度1 - AI售前工具应用
  • Description: AI自动抓取竞品优劣,生成售前差异化对比内容

When to Use

方案准备阶段,需要竞品对比分析时使用


Input Requirements

  • 竞品名称列表
  • 我方产品/方案资料
  • 对比维度要求(可选)

Workflow

  1. AI检索竞品公开资料(官网/产品文档/招标中标信息/媒体报道)
  2. 按功能、技术、价格、案例、服务、合规6个维度提取竞品信息
  3. 标注信息来源和时效性
  4. 与我方方案逐维度对比,标注优势/持平/劣势
  5. 提炼差异化卖点,输出竞争策略建议
  6. 生成竞品对比矩阵表

Output Format

竞品对比矩阵 + 差异化分析报告 + 竞争策略建议


Output Template

对比维度 | 我方 | 竞品A | 竞品B | 优势判断 | 差异化卖点

Example

字段 内容
技术架构 微服务+容器化

Constraints

  • 竞品信息标注来源和日期
  • 不确定信息标注'待验证'
  • 不得恶意贬低竞品

Quality Criteria

  • 对比维度完整
  • 信息来源可靠
  • 差异化卖点可落地

Applicable Scenarios

  • G端政府项目: 适用
  • B端企业项目: 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1: AI售前工具应用 | 编号: 005 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. 12d ago First seen · 88 lines · 0 tokens per session scan A e91bae446385

Subscribe to this mod's changes

005-Frank-AI竞品分析智能拆解工具 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 620 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 2026-08-30.

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