SEO Aeo Keyword Research
sickn33/agentic-awesome-skills
Researches and prioritises keywords from the site context and live search intent, including problem queries, question queries, difficulty tiers, and a content map.
Seerfar Ozon 关键词反查:按商品 SKU 列表(最多 20 个)反查 Ozon(及 Wildberries)搜索关键词,返回这些商品出现在哪些搜索词下(自然搜索词/广告搜索词),并按搜索热度、增长、商品数、卖家数、竞品数、自然排名、广告排名、曝光、转化、加购转化等多维指标筛选,每个关键词附带月搜热度、增长、市场空间、竞品/卖家数、均价、加购转化、Top…
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-search --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/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .claude/skills/linkfox-seerfar-ozon-keyword-back-search && 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 "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .claude/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-searchType 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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .agents/skills/linkfox-seerfar-ozon-keyword-back-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .agents/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .cursor/skills/linkfox-seerfar-ozon-keyword-back-search && 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 "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .cursor/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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/linkfox-ai/linkfox-skills.git --path skills/linkfox-seerfar-ozon-keyword-back-search--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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .gemini/skills/linkfox-seerfar-ozon-keyword-back-search && 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 "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .gemini/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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 linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-searchInstalls 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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .github/skills/linkfox-seerfar-ozon-keyword-back-search && 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 "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .github/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-seerfar-ozon-keyword-back-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/linkfox-seerfar-ozon-keyword-back-search .opencode/skills/linkfox-seerfar-ozon-keyword-back-search && 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 "linkfox-seerfar-ozon-keyword-back-search" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-seerfar-ozon-keyword-back-search into .opencode/skills/linkfox-seerfar-ozon-keyword-back-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-seerfar-ozon-keyword-back-search", 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.
linkfox-seerfar-ozon-keyword-back-searchSeerfar Ozon 关键词反查:按商品 SKU 列表(最多 20 个)反查 Ozon(及 Wildberries)搜索关键词,返回这些商品出现在哪些搜索词下(自然搜索词/广告搜索词),并按搜索热度、增长、商品数、卖家数、竞品数、自然排名、广告排名、曝光、转化、加购转化等多维指标筛选,每个关键词附带月搜热度、增长、市场空间、竞品/卖家数、均价、加购转化、Top…
Linkfox Seerfar Ozon Keyword Back Search is an agent skill from linkfox-ai/linkfox-skills. Seerfar Ozon 关键词反查:按商品 SKU 列表(最多 20 个)反查 Ozon(及 Wildberries)搜索关键词,返回这些商品出现在哪些搜索词下(自然搜索词/广告搜索词),并按搜索热度、增长、商品数、卖家数、竞品数、自然排名、广告排名、曝光、转化、加购转化等多维指标筛选,每个关键词附带月搜热度、增长、市场空间、竞品/卖家数、均价、加购转化、Top 商品及自然/广告渠道、排名、曝光、转化(dimension)等市场画像,用于 Ozon 关键词反查、Listing 选词优化、竞品流量词挖掘与广告词分析。当用户提到 Ozon 关键词反查、Ozon 反查关键词、Ozon SKU 反查、Ozon 商品流量词、Ozon 竞品出单词、Ozon 自然词/广告词反查、Seerfar Ozon、Ozon keyword back search, Ozon reverse keyword lookup, Ozon SKU keyword reverse 时触发此技能。即使用户未明确提到"Seerfar",只要其意图是按商品 SKU 反查 Ozon 搜索关键词并查看市场画像,也应触发此技能。
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/onboarding.py`).
The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 38fef04. It shows what the files ask for, not the result of running them.
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.
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
skill.linkfox.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
LINKFOX_AGENT_API_KEYLINKFOXAGENT_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Linkfox Seerfar Ozon Keyword Back Search loads about 2.9k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 135 tokens; SKILL.md has 1,309 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 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.
The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,309 words, ~2,938 tokens.
.claude/skills/linkfox-seerfar-ozon-keyword-back-search/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.This skill reverse-looks-up Ozon search keywords by a list of product SKU IDs in the Seerfar analytics database: pass up to 20 SKUs (your own listing or a competitor's) and it returns the search terms those products appear under — organic and/or ad — each enriched with a full market profile (search volume, 30-day growth, product/seller/competitor counts, average price, conversion concentration, top products, plus per-term organic/ad channel, natural rank, exposure, and conversion in the dimension object). It is the starting point for Ozon keyword reverse lookup, listing-title optimization, and competitor traffic-word discovery.
SKU-driven, not keyword-driven: unlike keyword mining (expand from a seed term) or market keyword search (browse the whole market), this endpoint takes skuIds and returns the search terms those specific products rank for. The direction is product → keywords (reverse).
hasVariant is required: every request must declare whether to exclude variants — 0 keep variants, 1 exclude variants. Pick 1 when you want de-duplicated keyword coverage for a parent listing.
Natural vs ad terms: type filters the search-term channel — ["0"] organic (自然搜索词) only, ["1"] ad (广告搜索词) only; omit to get both. Combine with the naturalRank / adRank range filters to qualify positioning.
Back-search metrics live in dimension: each returned term carries a dimension object with the reverse-lookup-specific metrics — type (0 organic / 1 ad), naturalRank (the SKU's natural rank for that term), exposure (exposure share, 0–1), conversion (conversion rate, 0–1), and x (opaque position indicator). The input filters type / naturalRank / adRank / exposure / conversion filter on these same per-term values. Note: relevancy is defined in the schema but is not returned by this endpoint.
Platform coverage: each keyword record carries a platform field (0 = Ozon, 1 = Wildberries). The dataset is Ozon-centric; Wildberries rows appear where available. There is no input to restrict the platform — filter client-side if needed.
Match mode: matchType controls how includeKeywords / excludeKeywords are matched — 0 exact, 1 fuzzy.
| Parameter | Type | Required | Description |
|---|---|---|---|
| skuIds | array<integer> | yes | Reverse-lookup SKU list, max 20. |
| hasVariant | integer | yes | Variant exclusion: 0 keep variants, 1 exclude variants. |
| page | object | yes | Pagination {page, pageSize, orders[]}. page from 1 (default 1), pageSize default 20. orders[] = {field, direction} with direction DESC/ASC. |
| matchType | integer | no | Keyword match mode: 0 exact, 1 fuzzy. |
| type | array<string> | no | Search-term channel filter: 0 organic, 1 ad; omit for both. |
| historyDate | string | no | Historical month yyyy-MM (e.g. 2026-02); omit for current period. |
| includeKeywords | array<string> | no | Terms that must appear (max 1000). |
| excludeKeywords | array<string> | no | Terms to exclude (max 1000). |
| searchVolume | {min,max} | no | Monthly search volume range. |
| searchChange30 | {min,max} | no | 30-day search change range. |
| wordCount | {min,max} | no | Keyword word/char count range. |
| productViews | {min,max} | no | Product view range. |
| products | {min,max} | no | Product count range. |
| sellers | {min,max} | no | Seller count range. |
| marketSpace | {min,max} | no | Market space range. |
| conversionSharing | {min,max} | no | Conversion concentration range. |
| uniqQueriesWCa | {min,max} | no | Cart-add count range. |
| ca | {min,max} | no | Cart-add conversion rate range. |
| conversion | {min,max} | no | Conversion rate range. |
| titleDensity | {min,max} | no | Title density range. |
| adRivalCount | {min,max} | no | Ad competitor count range. |
| adRank | {min,max} | no | Ad rank range. |
| naturalRank | {min,max} | no | Natural rank range. |
| exposure | {min,max} | no | Exposure range. |
| uId | string | no | User ID. |
| memberId | string | no | Member ID (data attribution). |
All range filters are {min, max} objects; supply either or both bounds. skuIds, hasVariant, and page are all required.
POST /seerfar/ozon/keywordBackSearch(完整参数/响应/错误码见 references/api.md)python scripts/seerfar_ozon_keyword_back_search.py '<JSON 参数>' [--inline]输出策略(脚本默认行为):
<cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-seerfar-ozon-keyword-back-search-<timestamp>.json(<cwd> 为脚本执行时的工作目录,在 Claude Code 里即当前项目目录;<session> 取自环境变量 SESSION_ID,按用户任务自动聚合;禁止写入 /tmp,当前目录不可写则报错)total/costToken、最大列表字段的长度 + 前 3 条样本)--inline 强制全量打印到 stdout(同样落盘)读数据建议:先看摘要判断是否足够;需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取,避免整份 JSON 进入上下文。
发生以下异常情况时,采用 references/onboarding.md 引导解决问题:
LINKFOX_AGENT_API_KEY,也未配置 LINKFOXAGENT_API_KEY。1. Reverse-lookup a single SKU's traffic keywords (sort by search volume)
{"skuIds": [4380710124], "hasVariant": 0, "page": {"page": 1, "pageSize": 10, "orders": [{"field": "searchVolume", "direction": "DESC"}]}}2. Organic terms where the SKU ranks near the top
{"skuIds": [4380710124], "hasVariant": 1, "type": ["0"], "naturalRank": {"max": 10}, "page": {"page": 1, "pageSize": 20, "orders": [{"field": "searchVolume", "direction": "DESC"}]}}3. Ad search words only, with an ad-rank floor
{"skuIds": [4380710124], "hasVariant": 0, "type": ["1"], "adRank": {"max": 50}, "page": {"page": 1, "pageSize": 20, "orders": [{"field": "searchVolume", "direction": "DESC"}]}}4. Narrow with include / exclude lists
{"skuIds": [4380710124], "hasVariant": 0, "page": {"page": 1, "pageSize": 20}, "includeKeywords": ["платье"], "excludeKeywords": ["ремень"], "matchType": 1}skuIds + hasVariant: both are required and define the reverse-lookup target. Use real Ozon SKU IDs (the same IDs returned by Seerfar Ozon product / shop / category skills).page.orders: sort by the metric you care about (searchVolume DESC for traffic weight, sellers ASC for low competition, count30GrowthRate DESC for rising terms).type: pass ["0"] or ["1"] to focus a listing-optimization pass (organic) or an ads pass (ad), then bound naturalRank / adRank to qualify positioning — these filter on the values surfaced in each row's dimension.includeKeywords / excludeKeywords to steer: force in must-have modifiers and strip noise without running a second query.query / queryCn (Chinese translation), then searchVolume, count30GrowthRate, productCount, sellers, avgPrice; show dimension.naturalRank and dimension.type (organic/ad) to convey how the SKU ranks for each term.query; the queryCn field provides a Chinese translation when available.type is omitted and both organic and ad rows are present, show dimension.type (0 organic / 1 ad) and dimension.naturalRank so the user can distinguish them.total is large, show the top rows and remind the user they can persist the full response via the large-response pattern below, or page further with page.page.code is not 200 (or errcode is not 200), explain the reason from msg / errmsg and suggest adjusting the SKU list or filters.skuIds + hasVariant + page required: a payload missing any of these is rejected.skuIds capped at 20: pass more than 20 and the request is rejected or truncated.keyword parameter — it is reverse (SKU → keywords), not expansion (keyword → keywords). Use the keyword mining skill to expand from a seed.searchDate / categories input: only historyDate (historical month) is accepted; there is no category filter. Use the market keyword search skill for month- or category-scoped browsing.products[*] (Top 商品) and dimension (per-term back-search metrics: type, naturalRank, exposure, conversion, x) are structured and decision-useful — see references/api.md for sub-fields. categoryInfos is defined in the schema/columns but is not returned in data[*] on this endpoint (same as the keyword-mining sibling; the market-keyword-search sibling does return it — don't assume parity). relevancy is likewise defined in the schema but not returned.Applicable — SKU-driven Ozon keyword reverse lookup:
| User Says | Scenario |
|---|---|
| "反查这个 Ozon 商品 / SKU 的关键词" | Reverse keyword lookup for a SKU |
| "这个 Ozon 链接有哪些搜索词带来流量" | Traffic-word discovery for a listing |
| "Ozon 竞品 SKU 的出单词 / 流量词" | Competitor traffic-word mining |
| "Ozon 某商品的自然词 / 广告词" | Organic vs ad term breakdown |
| "Ozon 关键词反查、按 SKU 反查关键词" | Generic reverse keyword lookup |
Not applicable — Needs beyond SKU-driven reverse lookup:
Boundary judgment: if the user has a product/SKU (own or competitor) and wants the search terms it ranks for, start here. If they want to browse the market (no SKU) or expand from a seed keyword, route to the market keyword search or keyword mining skill respectively.
消耗 23 算力。
用户会因算力消耗而支付费用。请充分评估:当需要高频调用本技能,或用户对算力消耗量预期不足时,务必提醒用户,由用户决定是否继续。
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
For more high-quality, professional cross-border e-commerce skills, set LinkFox Skills.
© linkfox-ai, 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 4 other files (scripts, references) in skills/linkfox-seerfar-ozon-keyword-back-search of linkfox-ai/linkfox-skills.
Open the folder on GitHubat commit 38fef04
Linkfox Seerfar Ozon Keyword Back Search 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 |
|---|---|---|---|---|---|---|
| Linkfox Seerfar Ozon Keyword Back Search this skilllinkfox-ai/linkfox-skills | 107 | — | ~2.9k | Automated safety check: Pass | MIT | |
| SEO Aeo Keyword Researchsickn33/agentic-awesome-skills | 47k | 1 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Keyword Extractorsickn33/agentic-awesome-skills | 47k | 2 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Keyword Researchaaron-he-zhu/aaron-marketing-skills | 2.9k | 1 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Keyword ResearchRyze-AI-Adgent/open-seo-mcp-skills | 4.7k | — | ~581 | Automated safety check: Pass | MIT | |
| Keyword Stuffingthedaviddias/Front-End-Checklist | 74k | — | ~896 | Automated safety check: Pass | MIT |
sickn33/agentic-awesome-skills
Researches and prioritises keywords from the site context and live search intent, including problem queries, question queries, difficulty tiers, and a content map.
sickn33/agentic-awesome-skills
Extracts up to 50 highly relevant SEO keywords from text. An agent skill from sickn33/agentic-awesome-skills.
aaron-he-zhu/aaron-marketing-skills
A skill your agent uses when the user asks to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data.
Ryze-AI-Adgent/open-seo-mcp-skills
Keyword research from a seed topic — ideas, real Google volume/CPC, intent, difficulty, clustered into a plan.
thedaviddias/Front-End-Checklist
A skill your agent uses when auditing content pages for over-optimisation, reviewing AI-generated content that may repeat target phrases excessively, or checking meta tags and alt text for unnatural…
thedaviddias/Front-End-Checklist
A skill your agent uses when applies to blog posts, product pages, and any content page with editable URL slugs.
linkfox-ai/linkfox-skills
1688平台以图搜图,通过商品图片精准检索外观相似或同款的1688货源,返回标题、价格、起批量、月销量、复购率、交易评分等核心数据。当用户提到1688以图搜图、1688找货源、以图找同款、跨境找工厂、1688识图、图片找货源、找相似货源、image search 1688、find supplier by…
linkfox-ai/linkfox-skills
亚马逊ABA(品牌分析)搜索词数据的查询与分析,涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean…
linkfox-ai/linkfox-skills
通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI…
linkfox-ai/linkfox-skills
亚马逊反向选品:基于历史商业洞察报告沉淀的指标数据池,按 30+ 项商业维度(市场规模与增长、价格区间与档位份额、竞争密度与头部集中度、人群画像如年龄/性别/收入、评论卖点与痛点等)反向筛选亚马逊赛道与关键词。当用户提到反向选品、指标筛选、细分市场反查、蓝海赛道挖掘、低竞争赛道、新人友好赛道、品牌分散市场、痛点切入、卖点反查、定价档位机会、人群画像选品、Amazon niche reverse…
linkfox-ai/linkfox-skills
通过ASIN获取亚马逊商品详细信息,包括标题、图片、五点描述、规格参数、A+页面、价格、评分评论、变体等;可在取得原始HTML时尝试提取Item Highlights(商品亮点)。当用户提到亚马逊商品详情、ASIN查询、商品页面数据、Listing分析、五点描述提取、Item…
linkfox-ai/linkfox-skills
按ASIN获取并分析亚马逊商品评论,支持15个站点(含美国站),按星级筛选评论。当用户提到亚马逊评论、美国站评论、商品评价、买家投诉、差评、好评、星级评分、评论分析、评论情感、产品改良建议、Vine评论、已验证购买评论、竞品评论研究、Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review…
Seerfar Ozon 关键词反查:按商品 SKU 列表(最多 20 个)反查 Ozon(及 Wildberries)搜索关键词,返回这些商品出现在哪些搜索词下(自然搜索词/广告搜索词),并按搜索热度、增长、商品数、卖家数、竞品数、自然排名、广告排名、曝光、转化、加购转化等多维指标筛选,每个关键词附带月搜热度、增长、市场空间、竞品/卖家数、均价、加购转化、Top…. Linkfox Seerfar Ozon Keyword Back Search is an agent skill from linkfox-ai/linkfox-skills.
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a claude-code`. Or copy the skill folder (skills/linkfox-seerfar-ozon-keyword-back-search in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-seerfar-ozon-keyword-back-search in your project. Claude Code loads it when a task matches its description.
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a codex`. Or copy the skill folder (skills/linkfox-seerfar-ozon-keyword-back-search in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-seerfar-ozon-keyword-back-search 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 linkfox-ai/linkfox-skills --skill linkfox-seerfar-ozon-keyword-back-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-seerfar-ozon-keyword-back-search, .gemini/skills/linkfox-seerfar-ozon-keyword-back-search, .github/skills/linkfox-seerfar-ozon-keyword-back-search and .opencode/skills/linkfox-seerfar-ozon-keyword-back-search in your project.
Going by SKILL.md and its folder, Linkfox Seerfar Ozon Keyword Back Search needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.
SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
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.
Linkfox Seerfar Ozon Keyword Back Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k 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 3.8k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Linkfox Seerfar Ozon Keyword Back Search: SEO Aeo Keyword Research (sickn33/agentic-awesome-skills, 47k stars), Keyword Extractor (sickn33/agentic-awesome-skills, 47k stars), Keyword Research (aaron-he-zhu/aaron-marketing-skills, 2.9k stars) and Keyword Research (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.
linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.
Source: linkfox-ai/linkfox-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.