Evaluate Skill
every-app/open-seo
Test a candidate OpenSEO skill end to end by running fresh, isolated Codex sessions against the local backend and scoring the reports they save.
基于Sorftime MCP的深度选品调研。通过LLM Agent执行多维度分析：数据采集→属性标注→交叉分析→竞品VOC→壁垒评估→选品决策评估。交互式执行，输出Markdown报告和Dashboard看板。
Install Product Research
$ npx skills add liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install liangdabiao/amazon-sorftime-research-MCP-skill product-research --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/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/SKILLS/skills/product-research .claude/skills/product-research && 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 "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .claude/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-researchType 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 liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install liangdabiao/amazon-sorftime-research-MCP-skill product-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/SKILLS/skills/product-research .agents/skills/product-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .agents/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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 liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install liangdabiao/amazon-sorftime-research-MCP-skill product-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/SKILLS/skills/product-research .cursor/skills/product-research && 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 "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .cursor/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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/liangdabiao/amazon-sorftime-research-MCP-skill.git --path SKILLS/skills/product-research--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 liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install liangdabiao/amazon-sorftime-research-MCP-skill product-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/SKILLS/skills/product-research .gemini/skills/product-research && 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 "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .gemini/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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 liangdabiao/amazon-sorftime-research-MCP-skill product-researchInstalls 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 liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/SKILLS/skills/product-research .github/skills/product-research && 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 "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .github/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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 liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install liangdabiao/amazon-sorftime-research-MCP-skill product-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/SKILLS/skills/product-research .opencode/skills/product-research && 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 "product-research" agent skill from https://github.com/liangdabiao/amazon-sorftime-research-MCP-skill/tree/main/SKILLS/skills/product-research into .opencode/skills/product-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-research", 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.
Facts
- Skill name
product-research- GitHub stars
- 959
- Used in
- 1 other repo
- Token cost
- ~3.5k tokens
- SKILL.md length
- 834 words
- Files
- 15 (incl. scripts, references)
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- None found
At a glance
基于Sorftime MCP的深度选品调研。通过LLM Agent执行多维度分析：数据采集→属性标注→交叉分析→竞品VOC→壁垒评估→选品决策评估。交互式执行，输出Markdown报告和Dashboard看板。
- Works in 7 steps: 信息收集 → 数据采集（增强版 v3.0） → 属性标注（LLM 驱动） → …
- Marketing & SEO work in your project
- SKILL.md covers 定位, Script Directory, 执行流程（两阶段） and 执行流程（交互式）, plus 8 more sections
- Runs Python scripts from its folder; calls python and curl; reaches mcp.sorftime.com
What it does
Product Research is an agent skill from liangdabiao/amazon-sorftime-research-MCP-skill. 基于Sorftime MCP的深度选品调研。通过LLM Agent执行多维度分析：数据采集→属性标注→交叉分析→竞品VOC→壁垒评估→选品决策评估。交互式执行，输出Markdown报告和Dashboard看板。
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts and reference files (for example `README.md`, `references/api-quick-reference.md` and `references/api-reference.md`).
It sits in Marketing & SEO. It works with Model Context Protocol. The repository describes itself as: 亚马逊选品 之 Listing全维度穿透分析报告 加上 全品类分析 ，关键词分析，差评分析 ，市场调研 等等。codex/claude code agent skill, amazon sorftime MCP/西柚mcp/sif mcp/卖家精灵sellersprite 智能体skill. 亚马逊跨境电商skill工具集。
When your agent uses it
- Marketing & SEO work in your project
Example prompts
- “/product-research”
Requirements
- Python 3
Workflow steps
7 steps, taken from the step headings in SKILL.md.
- 信息收集
- 数据采集（增强版 v3.0）
- 属性标注（LLM 驱动）
- 交叉分析（LLM 直接发现）
- 竞品与 VOC 分析
- 评估与决策
- 报告输出
What it can do on your machine
Read from SKILL.md and the folder at commit 568be29. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 8 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythoncurl
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
mcp.sorftime.com
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
Product Research loads about 3.5k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 31 tokens; SKILL.md has 834 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.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
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
Without a licence we can't republish the file, so here is its outline and opening line. It has 834 words (~3,534 tokens).
“基于 Sorftime MCP + LLM Agent 的深度选品调研。LLM 直接执行分析逻辑，脚本仅负责数据采集和报告渲染。”
- name
- product-research
- argument-hint
- [产品/类目关键词] [站点]
- user-invocable
- true
Files
SKILL.md and 14 other files (scripts, references) in SKILLS/skills/product-research of liangdabiao/amazon-sorftime-research-MCP-skill.
- SKILL.md
- README.md
- references/api-quick-reference.md
- references/api-reference.md
- references/prompt_templates.md
- references/sorftime-mcp-api.md
- references/troubleshooting.md
- scripts/api_client.py
- scripts/collect_data.py
- scripts/fix_data_json.py
- scripts/get_reviews.py
- scripts/render_dashboard.py
- scripts/run_analysis.py
- scripts/validate_data.py
- scripts/verify_reviews.py
Open the folder on GitHubat commit 568be29
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in liangdabiao/amazon-sorftime-research-MCP-skill, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Product Research 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 |
|---|---|---|---|---|---|---|
| Product Research this skillliangdabiao/amazon-sorftime-research-MCP-skill | 959 | 1 repos | ~3.5k | Automated safety check: Pass | None | |
| Evaluate Skillevery-app/open-seo | 23k | — | ~1.8k | Automated safety check: Notes | MIT | |
| Marketing PlanNexus-JPF/note-companion | 870 | 5 repos | ~5.2k | Automated safety check: Pass | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 799 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| AI VisibilityRyze-AI-Adgent/open-seo-mcp-skills | 4.7k | — | ~611 | Automated safety check: Pass | MIT | |
| Geo Scorejianruntech/geo-score | 582 | — | ~2.9k | Automated safety check: Pass | MIT |
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liangdabiao/amazon-sorftime-research-MCP-skill
亚马逊品类自动化选品分析技能。通过五维评分模型对亚马逊品类进行深度市场调研，生成Markdown分析报告。当用户使用 /category-selection 命令或提出'分析XX品类'、'XX品类市场调研'、'XX品类选品'等需求时触发此技能。支持配置分析数量，默认Top20。
Review Analysis
liangdabiao/amazon-sorftime-research-MCP-skill
对亚马逊商品评论进行深度分析，自动识别产品痛点、分析退货原因，生成改进建议和客服回复模板。Invoke when user uses /review-analysis command with a product ASIN.
Amazon Analyse
liangdabiao/amazon-sorftime-research-MCP-skill
对亚马逊竞品Listing进行全维度穿透分析，包括文案逻辑、评论分析、关键词分析、市场动态等。分析完成后自动保存为Markdown报告文档到reports/目录。Invoke when user uses /amazon-analyse command with a product ASIN.
Keyword Research
liangdabiao/amazon-sorftime-research-MCP-skill
亚马逊关键词深度调研与智能分类分析。基于 Sorftime MCP 数据采集 2000+ 关键词，通过 LLM Agent 按 8 维度智能分类（否定词、品牌词、材质词、场景词、属性词、功能词、核心词、其他），生成 Markdown 报告、CSV 词库和 HTML 仪表板。触发方式：/keyword-research {ASIN} {SITE}
Sellersprite Amazon Research
liangdabiao/amazon-sorftime-research-MCP-skill
卖家精灵 Amazon 全链路数据调研 Skill。通过 43 个 MCP 数据工具完成选品分析、关键词研究、竞品监控、市场分析、定价策略、评论分析、广告优化、流量分析、Listing 优化和蓝海机会挖掘。触发场景：(1) 用户询问 Amazon 选品/市场/竞品分析 (2) 用户输入 /product-research, /market-analysis…
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liangdabiao/amazon-sorftime-research-MCP-skill
基于西柚洞察MCP的亚马逊竞品分析与广告策略工具。提供7大核心工作场景：实时监控广告投放效果、快速找到高性价比流量缺口、快速拆解对标竞对打法、提升新品推广效率、精准拆解竞品流量以及广告策略、透视竞品广告策略和预算、高效搭建关键词库。适用于亚马逊卖家进行竞品分析、广告优化和关键词研究。
Related
Works with
Categories
Questions about Product Research
What does Product Research do?
基于Sorftime MCP的深度选品调研。通过LLM Agent执行多维度分析：数据采集→属性标注→交叉分析→竞品VOC→壁垒评估→选品决策评估。交互式执行，输出Markdown报告和Dashboard看板。. Product Research is an agent skill from liangdabiao/amazon-sorftime-research-MCP-skill.
When should I use Product Research?
Product Research fits situations like: marketing & SEO work in your project.
How do I install Product Research in Claude Code?
Run `npx skills add liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a claude-code`. Or copy the skill folder (SKILLS/skills/product-research in liangdabiao/amazon-sorftime-research-MCP-skill) into .claude/skills/product-research in your project. Claude Code loads it when a task matches its description.
How do I install Product Research in Codex?
Run `npx skills add liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a codex`. Or copy the skill folder (SKILLS/skills/product-research in liangdabiao/amazon-sorftime-research-MCP-skill) into .agents/skills/product-research in your project. Codex loads it when a task matches its description.
Can I use Product Research in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add liangdabiao/amazon-sorftime-research-MCP-skill --skill product-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-research, .gemini/skills/product-research, .github/skills/product-research and .opencode/skills/product-research in your project.
What does Product Research need to run?
Going by SKILL.md and its folder, Product Research needs Python for the scripts in its folder and the command-line tools its instructions call (python and curl). Our summary lists: Python 3.
Does Product Research access the network?
SKILL.md names 1 domain. In commands or code: mcp.sorftime.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Product Research safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. 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.
What licence does Product Research use?
No licence was found for Product Research or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Product Research use?
About 3.5k tokens (SKILL.md is roughly 14k 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 9.8k tokens, read only when the agent opens those files.
What are the alternatives to Product Research?
Skills that share tags, products or a category with Product Research: Evaluate Skill (every-app/open-seo, 23k stars), Marketing Plan (Nexus-JPF/note-companion, 870 stars), SEO Dataforseo (AgriciDaniel/codex-seo, 799 stars) and AI Visibility (Ryze-AI-Adgent/open-seo-mcp-skills, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Product Research?
liangdabiao (a GitHub user) maintains it in liangdabiao/amazon-sorftime-research-MCP-skill, which has 959 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 9, 2026.
Source: liangdabiao/amazon-sorftime-research-MCP-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.