Zach Search Term Analyzer

What it does

When your agent uses it

• Tasks that involve E-commerce operations

Example prompts

• “/zach-search-term-analyzer”

Requirements

• Python 3
• Pre-approved tools (allowed-tools): Read, Glob, Bash, Write, Edit, Grep

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1绝不捏造数据：所有分析数据来自用户提供的报告原始文件，没有数据就说"暂无"
2. 2缺失≠零：转化份额缺失/全 0 的词单列 B0"数据不足"，不参与象限判定，不得判为"转化差"
3. 3区分事实与推断：数据结论标「📊 数据事实」，策略建议标「💡 分析推断」
4. 4排名≠搜索量：搜索频率排名只表示相对位置
5. 5时效性：建议用最近 3-6 个月数据；强季节性产品参考上个旺季同期，且不同时段分开分析

What it can do on your machine

Read from SKILL.md and the folder at commit 5c790ea. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Glob
  • Bash
  • Write
  • Edit
  • Grep

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 2 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python3
  • pip3

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use pip3, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Zach Search Term Analyzer loads about 1.4k tokens when it runs, and up to ~6.6k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 349 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~71

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~6.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Glob, Bash, Write, Edit, Grep

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from zach22-1999/amazon-skills at commit 5c790ea, republished under its MIT licence (© zach22-1999). 349 words, ~1,373 tokens.

name

zach-search-term-analyzer

description

分析 Amazon Brand Analytics 热门搜索词报告（Top Search Terms）。场景化框架：自家 ASIN 在/不在该词点击 TOP3 走完全不同的业务判断（存量经营 vs 市场进入），确定性脚本输出场景状态、市场结构象限与成交系数，直接对接广告分池和 Listing 关键词布局。 使用时机：拿到 Brand Analytics Top Search Terms（热门搜索词）报告后，做关键词策略、市场进入判断或自家词份额监控。 触发词：/zach-search-term-analyzer

allowed-tools

Read, Glob, Bash, Write, Edit, Grep

triggers

/zach-search-term-analyzer

benefits-from

zach-product-research

user-invocable

true

risk-level

low

自家 ASIN ∈ 该词点击 TOP3 ？
├─ 是 → 场景 A：存量经营（看自家行 + 同词竞品行）
├─ 否 → 场景 B：市场进入（看 TOP3 合计的市场结构）
└─ 未提供自家 ASIN → 全部场景 B，报告显著标注"仅市场视角"

🧭 场景 A（自家 ASIN 已提供）：
🛡️ wireless speaker waterproof（A1收割词，自家系数1.3）→ 加预算防守
🔧 bluetooth speaker（A2漏水词，点击12.8% vs 转化6.1%）→ 先修详情页再抬价
🎯 同词竞品 B0XXXXXXXX 系数 0.4 → SP 商品定向截流

🧭 场景 B（市场进入）：
🌊 speaker with lights（B1机会词，集中度28%、满足度0.6）→ 属性一致则优先投放+进标题
🥷 party speaker（B4伏击词，集中度61%、满足度0.5）→ 竞品定向偷单，不打点击战
⛔ jbl speaker（B3头部满足词+垄断红线）→ 避其锋芒找长尾
❓ karaoke machine kids（B0数据不足）→ 转 SQP/广告数据验证

© zach22-1999, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/zach-search-term-analyzer of zach22-1999/amazon-skills.

• SKILL.md
• README.md
• references/关键词分类逻辑说明.md
• references/分析角度和方法.md
• references/字段说明.md
• scripts/analyze_search_terms.py
• scripts/requirements.txt

Open the folder on GitHubat commit 5c790ea