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Linkfox Sif Keyword Traffic

  • 159 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Helps with ai & agent building tasks.

About

linkfox-sif-keyword-traffic is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • linkfox-sif-keyword-traffic
  • AI & Agent Building
  • AI-coding skill

Linkfox Sif Keyword Traffic by the numbers

  • 159 all-time installs (skills.sh)
  • Ranked #3,263 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-sif-keyword-traffic

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Listed on Skillselion
Installs159
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

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):

1. Product-level fields (no prefix, e.g. naturalSearchExposureScore): the ASIN's overall exposure across all keywords. 2. Keyword-level fields (keyword… prefix, e.g. keywordNaturalExposureScore): the ASIN's exposure on just this one queried keyword.

Parameter Guide

Required Parameter

ParameterTypeDescription
searchKeywordstringThe search keyword to analyze. Translate to the target marketplace's language when applicable. Max 1000 characters.

Optional Parameters

ParameterTypeDefaultDescription
countrystringUSMarketplace code (13 supported — see list below).
asinsstring(none)Comma-separated ASIN filter; if omitted, returns all ASINs appearing under the keyword. Max 1000 chars.
conditionstring(none)Filter by a specific traffic source. Only one value per request. See Condition Filters below.
last7dbooleantrueUse the latest 7 days. When false, the API uses startDate/endDate.
startDatestringyyyy-MM-dd. Takes effect when last7d=false; if omitted, the system's latest integral week is used.
endDatestringyyyy-MM-dd, paired with startDate.
sortBystring(default)Sort field. See sortBy section below.
pageNuminteger1Page number for pagination.
pageSizeinteger100Results per page. Min 10, max 100.
descbooleantrueSort 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:

ValueMeaning
nfPositionNatural search traffic keywords
isSpAdSP ad keywords
isVedioAdVideo ad keywords
isBrandAdBrand ad keywords
isPPCAdPPC ad keywords (all paid ad types)
isSearchRecommendSearch recommendation keywords
acAdSP recommendation (Trending now / Customers frequently viewed / etc.)

Period-count filters (.total full / .in new-in):

ValueMeaning
totalPeriod.inNewly-entered traffic keywords this period
nfKeywordCnt.total / nfKeywordCnt.inKeywords with (new) organic exposure
adKeywordCnt.total / adKeywordCnt.inKeywords 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.

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/sif_keyword_traffic.py directly to run queries.

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: true

9. Newly-entered traffic keywords this period

searchKeyword: "wireless charger", country: "US", condition: "totalPeriod.in"

Display Rules

1. Present data clearly: Show query results in well-structured tables. Group data by traffic channel exposure ratios for easy comparison. 2. Distinguish product-level vs keyword-level scores: Do not mix naturalSearchExposureScore (product-wide) with keywordNaturalExposureScore (this keyword only). Label columns so users know which scope they are reading. 3. 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. 4. 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"). 5. Volume notice: When results are large (high total count), show core data and remind users they can paginate to see more results. 6. Period annotation: When comparing exposure/counts, label the resolved window — default last7d; or startDate ~ endDate if a custom range was set. Also surface dataPeriodStartDate on each row. 7. Error handling: When a query fails, explain the reason based on the msg field and suggest adjusting query parameters (e.g., checking keyword spelling or marketplace code). 8. Percentage formatting: Display exposure ratios as percentages (e.g., 0.45 as "45%") for readability. 9. 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 condition value 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 searchKeyword should 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 SaysScenario
"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)

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply: 1. The functionality or purpose described in this skill does not match actual behavior 2. The skill's results do not match the user's intent 3. The user expresses dissatisfaction or praise about this skill 4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

<!-- LF_LARGE_RESPONSE_BLOCK -->

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/sif_keyword_traffic.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"
Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

  • High field count per record, or fields you don't need
  • Batch/paginated results (multiple items per call)
  • Long-text fields (descriptions, reviews, HTML, time series)
  • Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read. <!-- /LF_LARGE_RESPONSE_BLOCK -->

--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).

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