Data Table Manager
n8n-io/n8n
Load before calling data-tables or parse-file. An agent skill from n8n-io/n8n.
分析 Amazon Ads SP / SB / SD 搜索词报告。确定性脚本负责清洗、时间窗聚合、词根聚类和决策计算,AI 助手或人工负责词根级语义分类;通过词根继承减少长尾词的待判定比例,输出 Markdown、CSV、HTML 和 JSON 六类结果。
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .claude/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .claude/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .agents/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .agents/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .cursor/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .cursor/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/zach22-1999/amazon-skills.git --path skills/zach-search-term-report-analyzer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .gemini/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .gemini/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .github/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .github/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zach22-1999/amazon-skills zach-search-term-report-analyzer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zach22-1999/amazon-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/zach-search-term-report-analyzer .opencode/skills/zach-search-term-report-analyzer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "zach-search-term-report-analyzer" agent skill from https://github.com/zach22-1999/amazon-skills/tree/main/skills/zach-search-term-report-analyzer into .opencode/skills/zach-search-term-report-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zach-search-term-report-analyzer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
zach-search-term-report-analyzer分析 Amazon Ads SP / SB / SD 搜索词报告。确定性脚本负责清洗、时间窗聚合、词根聚类和决策计算,AI 助手或人工负责词根级语义分类;通过词根继承减少长尾词的待判定比例,输出 Markdown、CSV、HTML 和 JSON 六类结果。
Zach Search Term Report Analyzer is an agent skill from zach22-1999/amazon-skills. 分析 Amazon Ads SP / SB / SD 搜索词报告。确定性脚本负责清洗、时间窗聚合、词根聚类和决策计算,AI 助手或人工负责词根级语义分类;通过词根继承减少长尾词的待判定比例,输出 Markdown、CSV、HTML 和 JSON 六类结果。 使用时机:判断搜索词是否应该否定、控成本、继续测试或放量,分析 7/14/30 天 CVR 与 ACOS 变化,或者提炼可反馈给 Listing 的属性词和场景词。 触发词:/zach-search-term-report-analyzer
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 36 other files, including scripts, reference files and assets (for example `README.md`, `examples/listing-context-sample.md` and `examples/root-classifications-sample.json`).
It sits in Documents & Office, covering E-commerce operations and CSV and tabular files. The repository describes itself as: Open-source Agent Skills for Amazon sellers: product research, feature validation, listing audits, ads search-term analysis, and CVR diagnostics. 亚马逊跨境电商 Skills。 The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 5c790ea. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBashGlobGrepFrom allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Zach Search Term Report Analyzer loads about 1.1k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 236 words of instructions outside code blocks.
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.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: Read, Write, Edit, Bash, Glob, GrepAutomated 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.
The full file from zach22-1999/amazon-skills at commit 5c790ea, republished under its MIT licence (© zach22-1999). 236 words, ~1,147 tokens.
.claude/skills/zach-search-term-report-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 32 other files; get the full folder from GitHub.v2 将确定性计算与语义判断分开:
搜索词报告
→ Stage A:清洗、7/14/30 天聚合、词根聚类、硬标签
→ Stage B:AI 助手或人工完成词根语义分类
→ Stage C:严格校验、词根决策继承、六类结果渲染词根继承用于处理低样本长尾词:当单个搜索词样本不足、但所属词根样本足够时,该词继承词根级判断;词与词根样本都不足时进入低量长尾池 pool,汇总监控但不伪装成待判定。
| 参数 | 必须 | 默认值 | 说明 |
|---|---|---|---|
| 搜索词报告 | 是 | — | CSV / XLSX / XLSM / XLS |
| ASIN | 是 | — | 一次只分析一个 ASIN |
| 品牌 | 是 | — | 用于品牌词硬标签与输出命名 |
| 目标 ACOS | 是 | — | 使用小数,例如 0.20 |
| 站点 | 否 | US | 用于可选的 Listing 上下文抓取 |
| 报告类型 | 否 | 自动识别 | SP / SB / SD |
| 时间窗 | 否 | 7,14,30 | 用逗号分隔 |
| Listing 上下文 | 否 | 空 | 可传入本地 Markdown / 文本快照 |
如果报告包含多个 ASIN,先从清洗元数据中列出候选,再让用户选定一个;不要混合分析。目标 ACOS、品牌或 ASIN 缺失时必须补齐,不能用隐藏默认值代替。
references/architecture.md — v2 管线、数据契约与决策顺序references/field_mapping.md — SP / SB / SD 字段映射references/decision_rules.md — 决策规则的运营解释references/term_classification.md — Stage B 分类枚举与 JSON schemareferences/output_template.md — 六类输出与完成信号scripts/prepare_search_term_analysis.py — Stage Ascripts/finalize_search_term_report.py — Stage Cscripts/clean_search_term_report.py — 清洗底层scripts/fetch_listing_context.py — 可选 Listing 上下文抓取python3 skills/zach-search-term-report-analyzer/scripts/prepare_search_term_analysis.py \
<input_file> \
--asin B0XXXXXXXX \
--brand ExampleBrand \
--site US \
--target-acos 0.20 \
--windows 7,14,30 \
--listing-context-file <optional-listing-context.md> \
--output-dir outputs/search-term-report-analyzer/ExampleBrand/intermediate/--listing-context-file 与 --report-type 均为可选参数,不使用时删除对应命令行。
Stage A 只做可复现计算:
asin_term 与 brand_term它会在中间目录生成:
workbook.json:term、root、窗口指标和分类请求roots_for_review.md:按花费排序的待分类词根表读取 roots_for_review.md、workbook.json 中的 Listing 上下文和 references/term_classification.md,为 classification_request.roots_to_classify 中每一个词根填写:
categoryrelevancenoteneeds_listing_check输出 root_classifications.json。示意结构:
{
"asin": "B0XXXXXXXX",
"classified_by": "ai_assistant",
"listing_context_source": "workbook.meta.listing_context",
"roots": {
"portable karaoke": {
"category": "core_category_term",
"relevance": "high",
"note": "与目标商品的核心用途直接一致",
"needs_listing_check": false
}
},
"term_overrides": {}
}分类纪律:
uncertain_term,必须给出 category 和 relevance。needs_listing_check 只用于少数确实依赖页面能力才能判断的词根。term_overrides。python3 skills/zach-search-term-report-analyzer/scripts/finalize_search_term_report.py \
outputs/search-term-report-analyzer/ExampleBrand/intermediate/workbook.json \
--classifications outputs/search-term-report-analyzer/ExampleBrand/intermediate/root_classifications.json \
--output-dir outputs/search-term-report-analyzer/ExampleBrand/Stage C 启动时会严格校验分类覆盖率和枚举值。校验通过后,每个搜索词得到一个主决策、一个决策依据层级 basis、置信度和原因。
输出目录建议为 outputs/search-term-report-analyzer/{brand}/:
| 文件 | 用途 |
|---|---|
..._搜索词报告分析.md | 主报告 |
..._搜索词分析明细.csv | 全词明细 |
..._否词清单.csv | exact 否词候选与 root 级 phrase 建议 |
..._搜索词分析操作台.html | 可筛选、排序、勾选和导出 CSV 的交互工作台 |
..._搜索词分析汇报.html | KPI、决策分布和花费去向静态汇报页 |
..._run_summary.json | 验收指标与文件清单 |
两个 HTML 都是自包含单文件,数据内联,无 CDN、Webfont、外链图片或运行时 fetch,可直接用浏览器打开。
读取 run_summary.json 并核对:
pending_ratio_terms 与 pending_ratio_spend 均不高于 0.10;超标必须解释。pool 的词数、点击、花费和订单在报告中单独披露,且不计入 pending。scripts/analyze_search_term_decisions.py 暂时保留,供已有自动化过渡使用,但已弃用。新任务只使用 Stage A → Stage B → Stage C;旧入口将在后续大版本移除。
© 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
SKILL.md and 32 other files (scripts, references, assets) in skills/zach-search-term-report-analyzer of zach22-1999/amazon-skills.
Open the folder on GitHubat commit 5c790ea
Zach Search Term Report Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Zach Search Term Report Analyzer this skillzach22-1999/amazon-skills | 209 | — | ~1.1k | Automated safety check: Notes | MIT | |
| Data Table Managern8n-io/n8n | 207k | — | ~2.3k | Automated safety check: Pass | Custom licence | |
| Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | 2 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Abuse Hunternexu-io/harness-engineering-guide | 664 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Intelligence Requirements BuilderTracecatHQ/tracecat | 3.8k | — | ~6k | Automated safety check: Pass | MIT | |
| Markitshift-labs-ai/markit | 1.3k | — | ~299 | Automated safety check: Pass | MIT |
n8n-io/n8n
Load before calling data-tables or parse-file. An agent skill from n8n-io/n8n.
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.
nexu-io/harness-engineering-guide
Detect and investigate bulk registration abuse on SaaS platforms.
TracecatHQ/tracecat
Turns a vague, high-level stakeholder ask into a structured set of intelligence requirements for a CTI team, complete with Essential Elements of Information, collection guidance, success criteria…
shift-labs-ai/markit
Convert files and URLs to Markdown. An agent skill from shift-labs-ai/markit.
tradermonty/claude-trading-skills
This skill should be used when analyzing sector rotation patterns and market cycle positioning.
zach22-1999/amazon-skills
亚马逊卖家专用的 skill 创建器(中文)。当用户想把一个亚马逊运营/自媒体/日常工作流程变成可复用的 skill 时使用。触发场景包括但不限于:用户说"我想做一个 skill""把这个流程变成 skill""帮我写个自动化""优化我已有的 skill""给这个工作流做个自动化",即使用户没用"skill"这个词,只要在描述"以后每次都这样做"的重复性工作时也应触发。本 skill…
zach22-1999/amazon-skills
功能需求真伪验证器。用三维数据(Review/关键词/社区)验证微创新是否真实需求. An agent skill from zach22-1999/amazon-skills.
zach22-1999/amazon-skills
基于领星 ASIN 360 或同类日业务报表,以及用户自己 SIF MCP 导出的日级关键词自然排名 JSON,回测 CVR 与核心词/稳定词自然排名波动的关系,并输出观察线、危险线、广告 CVR 确认线。
zach22-1999/amazon-skills
基于Sorftime MCP的选品分析,发现高潜力市场机会、多维度属性标注与交叉分析、验证竞争格局、测算投入产出、输出Go/No-Go决策与选品报告。
zach22-1999/amazon-skills
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。
zach22-1999/amazon-skills
以真实消费者视角检查亚马逊Listing健康状态。通过网页抓取模拟消费者浏览体验, 检查页面可见性、价格、卖家信息、购物车、配送、类目节点、排名、差评等关键指标, 并验证关键词搜索可见性。使用时机:新品上架后验收、日常巡检、排查Listing异常。
Categories
分析 Amazon Ads SP / SB / SD 搜索词报告。确定性脚本负责清洗、时间窗聚合、词根聚类和决策计算,AI 助手或人工负责词根级语义分类;通过词根继承减少长尾词的待判定比例,输出 Markdown、CSV、HTML 和 JSON 六类结果。. Zach Search Term Report Analyzer is an agent skill from zach22-1999/amazon-skills.
Zach Search Term Report Analyzer fits situations like: tasks that involve E-commerce operations; tasks that involve CSV and tabular files.
Run `npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a claude-code`. Or copy the skill folder (skills/zach-search-term-report-analyzer in zach22-1999/amazon-skills) into .claude/skills/zach-search-term-report-analyzer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a codex`. Or copy the skill folder (skills/zach-search-term-report-analyzer in zach22-1999/amazon-skills) into .agents/skills/zach-search-term-report-analyzer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zach22-1999/amazon-skills --skill zach-search-term-report-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/zach-search-term-report-analyzer, .gemini/skills/zach-search-term-report-analyzer, .github/skills/zach-search-term-report-analyzer and .opencode/skills/zach-search-term-report-analyzer in your project.
Going by SKILL.md and its folder, Zach Search Term Report Analyzer needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Zach Search Term Report Analyzer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 12k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Zach Search Term Report Analyzer: Data Table Manager (n8n-io/n8n, 207k stars), Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Abuse Hunter (nexu-io/harness-engineering-guide, 664 stars) and Intelligence Requirements Builder (TracecatHQ/tracecat, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
zach22-1999 (a GitHub user) maintains it in zach22-1999/amazon-skills, which has 209 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on August 20, 2026.
Source: zach22-1999/amazon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.