Sif Keyword Tracker
binggandata/bggg-skills
Sif 关键词动态跟踪（Skill 2）。同一 ASIN 有历史时由 sif-keyword-scout 自动触发， 按 1~7 天窗口对比 PD 主攻词单，输出词库更新报告。Agent 必须写 insightstracker.md， 且在写 insights 前完成暂停点 ③ 与用户确认投放策略。
在给定关键词下拆解所有竞品 ASIN 的流量来源——自然搜索、SP 广告、SB 品牌广告、SBV 视频广告、SP 推荐、AC/ER/TR 等推荐位，支持按 ASIN 过滤、指定日期区间及新进流量词等筛选。当用户提到关键词流量来源、该关键词下哪些竞品在抢流量、自然流量与付费流量占比、SP广告曝光、品牌广告占比、SP推荐位、推荐位广告/非广告拆分、搜索展示分析、Amazon's…
MITAuto-check passed
Install Linkfox Sif Keyword Summary
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-sif-keyword-summary -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sif-keyword-summary --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-sif-keyword-summary .claude/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .claude/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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-sif-keyword-summaryType 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-sif-keyword-summary -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sif-keyword-summary --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-sif-keyword-summary .agents/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .agents/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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-sif-keyword-summary -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sif-keyword-summary --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-sif-keyword-summary .cursor/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .cursor/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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-sif-keyword-summary--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-sif-keyword-summary -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install linkfox-ai/linkfox-skills linkfox-sif-keyword-summary --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-sif-keyword-summary .gemini/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .gemini/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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-sif-keyword-summaryInstalls 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-sif-keyword-summary -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-sif-keyword-summary .github/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .github/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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-sif-keyword-summary -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-sif-keyword-summary --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-sif-keyword-summary .opencode/skills/linkfox-sif-keyword-summary && 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-sif-keyword-summary" agent skill from https://github.com/linkfox-ai/linkfox-skills/tree/main/skills/linkfox-sif-keyword-summary into .opencode/skills/linkfox-sif-keyword-summary/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkfox-sif-keyword-summary", 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
linkfox-sif-keyword-summary- GitHub stars
- 107
- Used in
- 1 other repo
- Token cost
- ~3.1k tokens
- SKILL.md length
- 1,333 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 177
- Repo updated
- First seen
- Licence
- MIT
At a glance
在给定关键词下拆解所有竞品 ASIN 的流量来源——自然搜索、SP 广告、SB 品牌广告、SBV 视频广告、SP 推荐、AC/ER/TR 等推荐位，支持按 ASIN 过滤、指定日期区间及新进流量词等筛选。当用户提到关键词流量来源、该关键词下哪些竞品在抢流量、自然流量与付费流量占比、SP广告曝光、品牌广告占比、SP推荐位、推荐位广告/非广告拆分、搜索展示分析、Amazon's…
- Works in 2 steps: Product-level fields (no prefix, e.g.… → Keyword-level fields (keyword… prefix,…
- SKILL.md covers Core Concepts, Parameter Guide, 调用方式 and 解决认证和算力问题, plus 5 more sections
- Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY
What it does
Linkfox Sif Keyword Summary is an agent skill from linkfox-ai/linkfox-skills. 在给定关键词下拆解所有竞品 ASIN 的流量来源——自然搜索、SP 广告、SB 品牌广告、SBV 视频广告、SP 推荐、AC/ER/TR 等推荐位，支持按 ASIN 过滤、指定日期区间及新进流量词等筛选。当用户提到关键词流量来源、该关键词下哪些竞品在抢流量、自然流量与付费流量占比、SP广告曝光、品牌广告占比、SP推荐位、推荐位广告/非广告拆分、搜索展示分析、Amazon's Choice或编辑推荐曝光、关键词竞争格局、ASIN流量构成、keyword traffic, traffic structure analysis, search share, ad share, traffic source distribution, SIF, traffic analysis, SP recommendation, recommend position breakdown时触发此技能。即使用户未明确提及"SIF"，只要其需求涉及在某关键词下分析竞品 ASIN 的流量来源分布，也应触发此技能。
Its SKILL.md is about 3.1k 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.
Example prompts
- “/linkfox-sif-keyword-summary”
Requirements
- Python 3
- A credential in LINKFOX_AGENT_API_KEY
- A credential in LINKFOXAGENT_API_KEY
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Product-level fields (no prefix, e.g. naturalSearchExposureScore): the ASIN's overall exposure across all keywords.
- Keyword-level fields (keyword… prefix, e.g. keywordNaturalExposureScore): the ASIN's exposure on just this one queried keyword.
What it can do on your machine
Read from SKILL.md and the folder at commit 38fef04. 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 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
skill.linkfox.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
LINKFOX_AGENT_API_KEYLINKFOXAGENT_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkfox Sif Keyword Summary loads about 3.1k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 119 tokens; SKILL.md has 1,333 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
The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,333 words, ~3,117 tokens.
Download SKILL.mdSave it as
.claude/skills/linkfox-sif-keyword-summary/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- linkfox-sif-keyword-summary
- description
- 在给定关键词下拆解所有竞品 ASIN 的流量来源——自然搜索、SP 广告、SB 品牌广告、SBV 视频广告、SP 推荐、AC/ER/TR 等推荐位，支持按 ASIN 过滤、指定日期区间及新进流量词等筛选。当用户提到关键词流量来源、该关键词下哪些竞品在抢流量、自然流量与付费流量占比、SP广告曝光、品牌广告占比、SP推荐位、推荐位广告/非广告拆分、搜索展示分析、Amazon's Choice或编辑推荐曝光、关键词竞争格局、ASIN流量构成、keyword traffic, traffic structure analysis, search share, ad share, traffic source distribution, SIF, traffic analysis, SP recommendation, recommend position breakdown时触发此技能。即使用户未明确提及"SIF"，只要其需求涉及在某关键词下分析竞品 ASIN 的流量来源分布，也应触发此技能。
SIF Keyword Traffic Source Summary
This skill guides you on how to query and analyze keyword traffic source data for Amazon products, helping sellers understand the traffic structure behind keywords — including organic search, Sponsored Products (SP) ads, brand ads, video ads, and various Amazon recommendation placements.
Core Concepts
The SIF Keyword Summary tool returns, for one given keyword, the list of ASINs appearing under that keyword along with their per-keyword traffic exposure breakdown and their product-level cross-channel traffic mix. It answers: Who is taking traffic under this keyword, and through which channels?
Traffic channels analyzed:
- Natural Search — organic search result positions
- SP Ads (Sponsored Products) — paid product ad placements (regular slot)
- Brand Ads (SB) — top and bottom brand ad placements on the search results page
- Video Ads (SBV) — Sponsored Brands Video placements
- SP Recommendation slots — Trending now / Seen on social media / Customers frequently viewed / 4 stars and above
- Amazon's Choice (AC) — Amazon's Choice badge recommendations
- Editorial Recommendations (ER) — editorial/curated recommendation placements
- Top Rated (TR) — high-rating recommendation placements
Two score families (important — do not mix):
- Product-level fields (no prefix, e.g.
naturalSearchExposureScore): the ASIN's overall exposure across all keywords. - Keyword-level fields (
keyword…prefix, e.g.keywordNaturalExposureScore): the ASIN's exposure on just this one queried keyword.
Parameter Guide
Required Parameter
| Parameter | Type | Description |
|---|---|---|
| searchKeyword | string | The search keyword to analyze. Translate to the target marketplace's language when applicable. Max 1000 characters. |
Optional Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| country | string | US | Marketplace code (13 supported — see list below). |
| asins | string | (none) | Comma-separated ASIN filter; if omitted, returns all ASINs appearing under the keyword. Max 1000 chars. |
| condition | string | (none) | Filter by a specific traffic source. Only one value per request. See Condition Filters below. |
| last7d | boolean | true | Use the latest 7 days. When false, the API uses startDate/endDate. |
| startDate | string | — | yyyy-MM-dd. Takes effect when last7d=false; if omitted, the system's latest integral week is used. |
| endDate | string | — | yyyy-MM-dd, paired with startDate. |
| sortBy | string | (default) | Sort field. See sortBy section below. |
| pageNum | integer | 1 | Page number for pagination. |
| pageSize | integer | 100 | Results per page. Min 10, max 100. |
| desc | boolean | true | Sort in descending order. |
Supported Marketplaces
13 marketplaces: US (United States), UK (United Kingdom), DE (Germany), CA (Canada), JP (Japan), FR (France), ES (Spain), IT (Italy), MX (Mexico), AU (Australia), AE (United Arab Emirates), BR (Brazil), SA (Saudi Arabia).
Default marketplace is US. Codes outside this list will be rejected by the API pattern.
Condition Filters
Each request can include at most one condition filter. Flag-style:
| Value | Meaning |
|---|---|
| nfPosition | Natural search traffic keywords |
| isSpAd | SP ad keywords |
| isVedioAd | Video ad keywords |
| isBrandAd | Brand ad keywords |
| isPPCAd | PPC ad keywords (all paid ad types) |
| isSearchRecommend | Search recommendation keywords |
| acAd | SP recommendation (Trending now / Customers frequently viewed / etc.) |
Period-count filters (.total full / .in new-in):
| Value | Meaning |
|---|---|
| totalPeriod.in | Newly-entered traffic keywords this period |
| nfKeywordCnt.total / nfKeywordCnt.in | Keywords with (new) organic exposure |
| adKeywordCnt.total / adKeywordCnt.in | Keywords with (new) ad exposure |
| allSpKeywordCnt.total / allSpKeywordCnt.in | (New) SP-ad keywords (regular + recommendation) |
| spKeywordCnt.total / spKeywordCnt.in | (New) SP regular keywords |
| recSpKeywordCnt.total / recSpKeywordCnt.in | (New) SP recommendation keywords |
| allSbKeywordCnt.total / allSbKeywordCnt.in | (New) SB-ad keywords |
| sbKeywordCnt.total / sbKeywordCnt.in | (New) SB regular keywords |
| sbvKeywordCnt.total / sbvKeywordCnt.in | (New) SBV keywords |
sortBy
Leave empty for system default. Valid values:
totalKeywordNum (total keyword count), naturalKeywordNum, brandKeywordNum, vedioKeywordNum, acKeywordNum, erKeywordNum, trKeywordNum, sumScore (total exposure across all keywords), totalNfScore, totalSpSocre (note spelling), totalBrandScore, totalVedioScore, totalAcScore, totalTrScore, totalErScore.
调用方式
- API 端点：
POST /sif/keywordSummary（完整参数/响应/错误码见references/api.md） - Python 脚本：
python scripts/sif_keyword_traffic.py '<JSON 参数>' [--inline] - 成本约束：本工具会消耗算力；同一会话同一参数组合默认只调用一次，脚本带 24h 本地缓存。失败/空结果不得自动换关键词、翻页或改邮编连续试探；需要继续检索时先向用户说明会产生额外消耗。
输出策略（脚本默认行为）：
- 始终将完整响应写入
<cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-sif-keyword-summary-<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） - 响应体 ≤ 8 KB：落盘后把完整 JSON 打印到 stdout
- 响应体 > 8 KB：落盘后 stdout 只输出摘要（顶层字段、常见计数如
total/costToken、最大列表字段的长度 + 前 3 条样本） - 加
--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。
解决认证和算力问题
发生以下异常情况时，采用 references/onboarding.md 引导解决问题：
异常情况
- 未配置API Key：环境变量未配置
LINKFOX_AGENT_API_KEY，也未配置LINKFOXAGENT_API_KEY。 - 响应401或402状态码
- 响应提示算力或余额不足：消息含"算力余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值"，或类似含义的内容。
Usage Examples
1. Basic keyword traffic overview Query the traffic source breakdown for a keyword in the US marketplace:
searchKeyword: "wireless charger", country: "US"2. Filter for organic search traffic only See only ASINs that appear in natural search results for a keyword:
searchKeyword: "wireless charger", country: "US", condition: "nfPosition"3. Analyze SP ad competition Find which ASINs are running SP ads for a keyword:
searchKeyword: "wireless charger", country: "US", condition: "isSpAd"4. SP recommendation slots Find ASINs surfacing in SP recommendation slots (Trending now, Customers frequently viewed, etc.):
searchKeyword: "wireless charger", country: "US", condition: "acAd"5. Keyword analysis for a non-US marketplace Analyze traffic sources in the Japan marketplace (use the local language keyword):
searchKeyword: "ワイヤレス充電器", country: "JP"6. Focus on specific competitor ASINs Limit results to a small set of competing ASINs:
searchKeyword: "wireless charger", country: "US", asins: "B01NBNDC1T,B09VLJJPL6"7. Custom date range
searchKeyword: "wireless charger", country: "US", last7d: false, startDate: "2026-04-05", endDate: "2026-04-11"8. Rank ASINs by their overall SP exposure
searchKeyword: "wireless charger", country: "US", sortBy: "totalSpSocre", desc: true9. Newly-entered traffic keywords this period
searchKeyword: "wireless charger", country: "US", condition: "totalPeriod.in"Show full SKILL.md (600 more words)Show less
Display Rules
- Present data clearly: Show query results in well-structured tables. Group data by traffic channel exposure ratios for easy comparison.
- Distinguish product-level vs keyword-level scores: Do not mix
naturalSearchExposureScore(product-wide) withkeywordNaturalExposureScore(this keyword only). Label columns so users know which scope they are reading. - Highlight key ratios: When displaying results, emphasize the natural search exposure ratio vs. paid ad exposure ratio to help users quickly assess the organic-to-paid balance.
- Translate field names: Present field names in user-friendly language rather than raw API field names (e.g., "Natural Search Exposure Ratio" instead of "naturalSearchExposureRatio").
- Volume notice: When results are large (high total count), show core data and remind users they can paginate to see more results.
- Period annotation: When comparing exposure/counts, label the resolved window — default
last7d; orstartDate ~ endDateif a custom range was set. Also surfacedataPeriodStartDateon each row. - Error handling: When a query fails, explain the reason based on the
msgfield and suggest adjusting query parameters (e.g., checking keyword spelling or marketplace code). - Percentage formatting: Display exposure ratios as percentages (e.g., 0.45 as "45%") for readability.
- Traffic source summary: When presenting a single ASIN's data, provide a brief traffic composition summary (e.g., "This product gets 60% of its exposure from organic search, 25% from SP ads, and 15% from brand ads"); prefer keyword-level fields when the user asks specifically about this keyword.
Important Limitations
- Single condition filter: Only one
conditionvalue can be used per request. To compare multiple traffic sources, make separate requests. - Marketplace coverage: 13 marketplaces only — IN / NL / SE / PL / TR / SG are no longer available.
- Keyword language: The
searchKeywordshould be in the language of the target marketplace for best results. - Result cap: Each page returns at most 100 records.
- Scope: This endpoint focuses on per-keyword ASIN traffic; it does not return whole-ASIN metadata, cross-channel keyword counts, or variant aggregation. Use the ASIN traffic-source tool for those.
User Expression & Scenario Quick Reference
Applicable — Traffic source and competition structure analysis for Amazon keywords:
| User Says | Scenario |
|---|---|
| "Where does the traffic come from for this keyword" | Traffic source breakdown |
| "How much organic vs paid traffic" | Organic/paid ratio analysis |
| "Who's running SP ads for this keyword" | SP ad competition analysis (condition=isSpAd) |
| "Which products are in SP recommendation slots" | SP recommendation lookup (condition=acAd) |
| "Which products have Amazon's Choice" | AC badge analysis (via amazonsChoiceExposureScore) |
| "Is this keyword dominated by ads" | Ad saturation assessment |
| "Show me the brand ad competition" | Brand ad landscape analysis |
| "Traffic structure for my competitor's keyword" | Competitive traffic analysis |
| "Which products get editorial recommendations" | ER placement analysis |
| "Compare these 2 ASINs on this keyword" | ASIN filter via asins="B0A,B0B" |
| "For the week of March 8, traffic under this keyword" | Custom startDate/endDate window |
| "Newly-entered traffic keywords this period" | New-in filter (condition=totalPeriod.in) |
Not applicable — Needs beyond keyword traffic source analysis:
- Historical keyword ranking trends beyond current + custom window (use ABA data tools)
- Advertising bid/budget optimization
- Product reviews or listing content
- Sales volume estimation
- Full keyword search volume curve over time
- Whole-ASIN traffic structure across all keywords (use the SIF ASIN traffic-source tool)
算力消耗规则
消耗 9 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:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
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© 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
Files
SKILL.md and 4 other files (scripts, references) in skills/linkfox-sif-keyword-summary of linkfox-ai/linkfox-skills.
- SKILL.md
- references/api.md
- references/onboarding.md
- scripts/onboarding.py
- scripts/sif_keyword_traffic.py
Open the folder on GitHubat commit 38fef04
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 linkfox-ai/linkfox-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Linkfox Sif Keyword Summary 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 Sif Keyword Summary this skilllinkfox-ai/linkfox-skills | 107 | 1 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Sif Keyword Trackerbinggandata/bggg-skills | 605 | — | ~383 | Automated safety check: Pass | MIT | |
| Sif Keyword Scoutbinggandata/bggg-skills | 605 | — | ~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 | |
| Speak Summarygithub/awesome-copilot | 40k | — | ~1.6k | Automated safety check: Pass | MIT |
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Questions about Linkfox Sif Keyword Summary
What does Linkfox Sif Keyword Summary do?
在给定关键词下拆解所有竞品 ASIN 的流量来源——自然搜索、SP 广告、SB 品牌广告、SBV 视频广告、SP 推荐、AC/ER/TR 等推荐位，支持按 ASIN 过滤、指定日期区间及新进流量词等筛选。当用户提到关键词流量来源、该关键词下哪些竞品在抢流量、自然流量与付费流量占比、SP广告曝光、品牌广告占比、SP推荐位、推荐位广告/非广告拆分、搜索展示分析、Amazon's…. Linkfox Sif Keyword Summary is an agent skill from linkfox-ai/linkfox-skills.
How do I install Linkfox Sif Keyword Summary in Claude Code?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-sif-keyword-summary -a claude-code`. Or copy the skill folder (skills/linkfox-sif-keyword-summary in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-sif-keyword-summary in your project. Claude Code loads it when a task matches its description.
How do I install Linkfox Sif Keyword Summary in Codex?
Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-sif-keyword-summary -a codex`. Or copy the skill folder (skills/linkfox-sif-keyword-summary in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-sif-keyword-summary in your project. Codex loads it when a task matches its description.
Can I use Linkfox Sif Keyword Summary 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 linkfox-ai/linkfox-skills --skill linkfox-sif-keyword-summary -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-sif-keyword-summary, .gemini/skills/linkfox-sif-keyword-summary, .github/skills/linkfox-sif-keyword-summary and .opencode/skills/linkfox-sif-keyword-summary in your project.
What does Linkfox Sif Keyword Summary need to run?
Going by SKILL.md and its folder, Linkfox Sif Keyword Summary 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.
Does Linkfox Sif Keyword Summary access the network?
SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.
Is Linkfox Sif Keyword Summary 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 Linkfox Sif Keyword Summary use?
Linkfox Sif Keyword Summary is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Linkfox Sif Keyword Summary use?
About 3.1k 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 3.2k tokens, read only when the agent opens those files.
What are the alternatives to Linkfox Sif Keyword Summary?
Skills that share tags, products or a category with Linkfox Sif Keyword Summary: Sif Keyword Tracker (binggandata/bggg-skills, 605 stars), Sif Keyword Scout (binggandata/bggg-skills, 605 stars), SEO Aeo Keyword Research (sickn33/agentic-awesome-skills, 47k stars) and Keyword Extractor (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkfox Sif Keyword Summary?
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.