zoodata
>
pinned to #806502dupdated 3 weeks ago
Ask your AI client: “install skills/zoodata”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/zoodatametahub onboarded this repo on the author's behalf.
If you own github.com/SerendipityOneInc/APIClaw-Skills on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
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- #ai-agent
- #ai-agents
- #amazon
- #amazon-api
- #amazon-seller
- #api
- #clawhub
- #commerce-data
- #ecommerce
- #mcp
- #mcp-server
- #product-research
- #python
- #skills
About this skill
Pulled from SKILL.md at publish time.
> **📋 Live API Reference**: Field names and parameters may change. If you encounter field errors, > check the latest OpenAPI spec at https://zoodata.ai/api/v1/openapi-spec for current field definitions.
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.806502d· 3 weeks ago
Documentation
41Description qualitywarn
10 words · 66 chars — skills use the description as their trigger; aim higher — manifest description is empty; graded the GitHub repo description instead
Aim for 15+ words and include trigger phrases like “use this skill when …”.
README is present and substantial
14,238 chars · 10 sections · 5 code blocks
Tags / topics declared
14 total — ai-agent, ai-agents, amazon, amazon-api, amazon-seller, api (+8)
README has usage / example sections
found: Quick Start
Homepage / docs URL declared
https://apiclaw.io/
Release history
1- releasecurrent806502dwarn3 weeks ago
Contents
📋 Live API Reference: Field names and parameters may change. If you encounter field errors, check the latest OpenAPI spec at https://zoodata.ai/api/v1/openapi-spec for current field definitions.
ZooData — Commerce Data Infrastructure for AI Agents
200M+ Amazon products. 20 endpoints. One API key.
Quick Start
- Get key: zoodata.ai/api-keys (1,000 free credits)
export ZOODATA_API_KEY='hms_live_xxx'- Base URL:
https://api.zoodata.ai/openapi/v2— all POST with JSON body - Auth:
Authorization: Bearer YOUR_API_KEY - New keys need 3-5s to activate. If 403, wait and retry.
⚠️ Critical API Pitfalls (ALL skills must follow)
- Keyword search is broad → MUST lock
categoryPathfirst viacategoriesendpoint - Brand/price-band queries MUST include --category to avoid cross-category contamination
- Revenue =
sampleAvgMonthlyRevenuedirectly. NEVER calculate avgPrice × totalSales (overestimates 30-70%) - Sales =
monthlySalesFloor(lower bound). Fallback: 300,000 / BSR^0.65, tag as 🔍 - Use API fields directly:
sampleOpportunityIndex,sampleTop10BrandSalesRate— never reinvent - reviews/analysis needs 50+ reviews. Fallback chain when sample is insufficient:
- Lightweight:
realtime/product→ratingBreakdown(star distribution only, no themes) - Full 11-dim insights:
realtime/reviews(raw text, up to 100) + local Map/Reduce via the Local Review Toolkit below — see "Local Review Toolkit" section
- Lightweight:
- Aggregation endpoints (price-band, brand) without categoryPath produce severely distorted data
- Price-band and brand endpoints only accept
keyword(not categoryPath) — cross-validate returned products
On Missing Key (no credentials configured)
BEFORE calling any endpoint, verify credentials are configured. The reliable check is python {skill_base_dir}/scripts/zoodata.py check — credentials-only by default, no endpoint calls and no credit usage; exits non-zero if no key is found in env vars OR config files. A [ -z "$ZOODATA_API_KEY" ] test alone is NOT sufficient — a user may have only ~/.zoodata/config.json set.
When no key is found through any mechanism:
- STOP. Do not run the workflow. Do not call
zoodata.py(you'll just get the same credential error and burn tokens). - Do NOT fall back to a "partial analysis from training data" / "industry common-sense headlines" / "for reference only" preview. Your training data is stale, has no per-ASIN granularity, and presenting it as analysis — even disclaimed — misrepresents what this skill produces. The deliverable is data-backed; without data, there is no deliverable.
- Tell the user, in their language, all three of:
- "
ZOODATA_API_KEYis not set — I need this to run the analysis." - Get a free key (1,000 credits, no credit card): https://zoodata.ai/en/api-keys
- Configure via one of:
export ZOODATA_API_KEY='hms_live_xxx'(session only)mkdir -p ~/.zoodata && echo '{"api_key":"hms_live_xxx"}' > ~/.zoodata/config.json(persistent)
- "
- Optionally state in one sentence what the workflow will produce once the key is configured (deliverable shape only — no numbers, no market color, no "common sense" preview).
On 401 Invalid Key
When zoodata.py returns {"code": 401, "message": "API Key invalid or expired"}:
- STOP further endpoint calls immediately. Do not retry — a rejected key won't be accepted on a second try; every subsequent call will return 401 too.
- Report to the user:
- The
ZOODATA_API_KEYin use was rejected (likely invalid, revoked, or expired) - If any partial findings were collected before the failure, show them and mark as partial
- Fix at https://zoodata.ai/en/api-keys (verify the key, regenerate if needed)
- The
- Do not fabricate or guess the data the failed calls would have returned. This includes "training-data fallback" / "industry common-sense" headlines disguised as preview — those are fabrications.
On 402 Credit Exhausted
When zoodata.py returns {"code": 402, "message": "API quota exhausted or subscription expired"}:
- STOP further endpoint calls immediately. Do not retry. Do not switch endpoints as a workaround — 402 is account-level (key/subscription), not endpoint-level.
- Report to the user with all four of:
- Which step in the workflow was reached (e.g. "Completed step 3/5: brand analysis")
- Partial findings already collected (show the actual data, not just a list of completed steps)
- Rough credits needed to resume (sum remaining-step costs from this skill's API Budget table)
- Top-up link: https://zoodata.ai/en/pricing
- Do not fabricate or guess the missing data to "complete" the report. Mark partial findings explicitly as partial. No "training-data fallback" / "industry common-sense" filler — substituting public-knowledge prose for missing endpoint data is still fabrication.
20 Endpoints
| # | Endpoint | Purpose | Key Output |
|---|---|---|---|
| 1 | categories | Browse/search category tree | categoryPath, productCount |
| 2 | markets/search | Market-level metrics | sampleAvgMonthlySales, sampleAvgPrice, topSalesRate, sampleNewSkuRate |
| 3 | products/search | Product search (14 modes) | asin, price, monthlySalesFloor, rating, ratingCount, fbaFee |
| 4 | products/competitors | Competitor discovery | same fields as products/search |
| 5 | realtime/product | Live ASIN detail | rating, features, bestsellersRank[], buyboxWinner.price, variants |
| 6 | reviews/analysis | AI review insights (11 dims) | sentimentDistribution, consumerInsights, topKeywords |
| 7 | realtime/reviews | Live raw review text (cursor paginated, max 100) | reviews[], nextCursor — feeds Local Review Toolkit |
| 8 | products/price-band-overview | Price band summary | hottestBand, bestOpportunityBand, sampleOpportunityIndex |
| 9 | products/price-band-detail | Full 5-band distribution | priceBands[] with sales, brands, ratings per band |
| 10 | products/brand-overview | Brand concentration | sampleTop10BrandSalesRate (CR10), sampleBrandCount |
| 11 | products/brand-detail | Per-brand breakdown | brands[] with sales, revenue, sampleProducts |
| 12 | products/history | Time series (single ASIN per call) | timestamps[], price[], bsr[], monthlySalesFloor[], rating[], ratingCount[], sellerCount[], title/imageUrl/bestSeller/newRelease/aPlus/inventoryStatus changelogs |
| 13 | /openapi/v2/keywords/detail | Keyword summary from the nearest available weekly snapshot | estimateSearchCountWeekly, abaRank, marketCharacteristics, adCount; may return data: null |
| 14 | /openapi/v2/keywords/trend | Weekly keyword time series | estimateSearchCount, abaRank, rankChangeCount, periodStartDate, periodEndDate |
| 15 | /openapi/v2/keywords/extends | Keyword expansion / long-tail discovery | related keywords ranked by relevanceScore / estimateSearchCount; may return empty array |
| 16 | /openapi/v2/keywords/search-results | Daily keyword SERP snapshot | asin, exploreType, absolutePosition, estimateImpressionPoint, listing fields |
| 17 | /openapi/v2/keywords/competitor-product-keywords | Keyword set where an ASIN appears as a competitor | keyword, avgPosition, keywordEstimateSearchCount, trafficShare |
| 18 | /openapi/v2/keywords/product-traffic-terms | Traffic-driving keywords for an ASIN | same live response shape as competitor-product-keywords |
| 19 | /openapi/v2/keywords/product-traffic-terms-overview | Weekly ASIN all-keyword traffic-change overview | current vs previous-period placement-level impression points, ORG first-3-page keyword entries/exits |
| 20 | /openapi/v2/keywords/product-traffic-terms-timeline | ASIN + keyword daily timeline | position/impression points, listing snapshot, keyword weekly metrics, ad activity |
Known Quirks
topN,listingAge,newProductPeriodare strings ("10"not10)- Many search/list endpoints return
.dataas an array — use.data[0]for the first record. But some commands may return non-array payloads insidedata, so inspect the actual response shape before indexing. ratingCountnotreviewCounteverywherebsr(int) in products vsbestsellersRank(array) in realtimebuyboxWinner.price— NOT top-levelpricein realtimerealtime/productdoes NOT return: monthlySalesFloor, fbaFee, sellerCountreviewCountMin/Maxfilters currently broken (API-56)reviews/analysismay 500 for certain ASINs (API-58) — retry different ASIN- Rate limit: 100 req/min, 10 req/sec burst
categoriesusescategoryKeyword(notkeyword) andparentCategoryPath(notparentCategoryName)reviews/analysis:moderequired ("asin"/"category"), useasins(plural array) notasinrealtime/reviews: returns 10 reviews/page fixed (nopageSizeparam); 1 credit/page; cursor-paginated; hard cap = 100 reviews (10 pages); supportsmarketplaceUS/UK onlykeywords/detailresolves the inputdateto the nearest available weekly snapshot at or before that date, and may legitimately returndata: nulleven withsuccess: truekeywords/extendsalso resolves the inputdateto the nearest available weekly snapshot, requiresquery(notkeyword), supportsqueryType=phraseorfuzzy, and may legitimately returndata: []keywords/search-results,keywords/competitor-product-keywords, andkeywords/product-traffic-termsuse daily observations over a sliding ~7-day window, not a long-retention historical store- Keyword endpoints are keyword-query workflows; for inputs named
keywordorquery, use the Amazon search query / keyword phrase being analyzed - For keyword endpoints that require
dateordateTo, prefer T-1 or earlier and avoid the current date unless the user explicitly asks for today's lookup keywords/search-resultsrequiresdate+keyword;exploreTypesvalues areORG,SP,SB,SBV,SPRkeywords/competitor-product-keywordsandkeywords/product-traffic-termsrequiredate+asin; both currently return the same live item shape, includingtrafficSharekeywords/product-traffic-terms-overviewrequiresdate+asin; it returns the latest weekly overview of all keyword impression traffic changes under that ASIN at or before the date, compared with the previous periodkeywords/product-traffic-terms-timelinerequiresasin+ exactkeyword+dateFrom+dateTo; the date range cannot exceed 60 dayskeywords/search-resultsis the default source for explaining what products currently appear on a keyword SERP because it already returns listing-level product fieldsproducts/searchis a broader ZooData product-database query and must not be presented as Amazon live keyword SERP ordering
Keyword Intelligence Endpoints
These eight endpoints were verified against the live API surface and fill the gap between raw catalog data and search-demand/search-visibility intelligence.
Keyword value boundary:
- Keyword endpoints provide estimated search, visibility, rank, traffic-share, and impression-point signals
- They do not provide a seller's first-party ABA Search Query Performance funnel by themselves
- Treat keyword value, profitability, and conversion potential as directional unless the user supplies ABA-SQP impressions, clicks, cart adds, purchases, click share, purchase share, and conversion rate
- ABA-SQP backend location: Chinese Seller Central path
品牌分析 -> 搜索分析 -> 搜索查询绩效 -> 品牌视图; English Seller Central pathBrand Analytics -> Search Analytics -> Search Query Performance -> Brand View - Recommended ABA-SQP data provision method: in Brand View, sort descending by
[Search Funnel - Impressions](https://sellercentral.amazon.com/brand-analytics/metric-glossary?linkedFrom=query-performance-brand-report-table-qp-impressions-group) -> Brand Count/搜索漏斗-展示次数 -> 品牌数量, then provide a screenshot; alternatively, download the CSV and provide it for model analysis - If the user has not provided Amazon backend ABA-SQP search conversion data, every traffic-related conclusion or recommendation group should include: "建议结合 Amazon 后台 ABA-SQP 的搜索转化数据做更精确分析(中文路径:品牌分析 -> 搜索分析 -> 搜索查询绩效 -> 品牌视图;英文路径:Brand Analytics -> Search Analytics -> Search Query Performance -> Brand View)."
- If the user provided ABA-SQP data, use it as first-party conversion evidence and do not add that caveat
/openapi/v2/keywords/detail
- Input:
keyword,date, optionalmarketplace - Data window: resolves the requested
dateto the nearest available weekly snapshot at or before that date - Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape: top-level
datais an object ornull(not an array) - Key fields from schema:
estimateSearchCountWeekly,abaRank,abaTop3ClickShareRate,abaTop3ConversionShareRate,marketCharacteristics,totalSkuCnt,brandCount,organicSkuCount,adCampaignCount,adCount - Live validation note: for
keyword="yoga mat"and several June 2026 dates, the endpoint returnedsuccess: truewithdata: null
/openapi/v2/keywords/trend
- Input:
keyword,dateFrom,dateTo, optionalmarketplace - Data window: weekly-granularity points across the requested date range
- Date rule: prefer T-1 or earlier for
dateTo; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Key fields from live response/schema:
observedAt,periodStartDate,periodEndDate,estimateSearchCount,estimateSearchChangeCount,estimateSearchChangeRate,abaRank,prevAbaRank,prevEstimateSearchCount,rankChangeCount
/openapi/v2/keywords/extends
- Input:
query,date, optionalmarketplace,page,pageSize,queryType,sortBy,sortOrder - Important quirk: seed field is
query, notkeyword;queryTypesupportsphraseandfuzzy - Data window: resolves the requested
dateto the nearest available weekly snapshot at or before that date - Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Key fields from schema:
term,seedKeyword,relevanceScore,estimateSearchCountWeekly,abaRank,marketCharacteristics,brandCount,organicSkuCount,adCount,periodStartDate,periodEndDate,observedAt - Live validation note: empty arrays are normal;
query="yoga mat"returneddata: []for bothqueryType="phrase"andqueryType="fuzzy"
/openapi/v2/keywords/search-results
- Input:
keyword,date, optionalmarketplace,page,pageSize,exploreTypes,sortBy,sortOrder - Data window: daily observations surfaced through a sliding ~7-day window
- Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Key fields from live response/schema:
exploreType,absolutePosition,pageIndex,pagePosition,asin,title,brand,price,currency,link,imageLink,rating,ratingCount,recentSales,hasVideo,estimateImpressionPoint,keywordTotalEstimateImpressionPoint - Interpretation rule: use this endpoint first for "what is on page 1 / what products dominate this keyword / what does the SERP look like"
- Do not substitute
products/searchwhen the question is about observed keyword SERP composition or ordering
/openapi/v2/keywords/competitor-product-keywords
- Input:
asin,date, optionalmarketplace,page,pageSize,exploreTypes,keywordContains,sortBy,sortOrder - Data window: daily observations surfaced through a sliding ~7-day window
- Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Key fields from live response/schema:
exploreType,absolutePosition,pageIndex,pagePosition,asin,keyword,estimateImpressionPoint,asinTotalEstimateImpressionPoint,avgPosition,daysCoverageRate,observationCount,keywordEstimateSearchCount,keywordEstimateSearchGrowthCount,keywordEstimateSearchCountChangeRate,keywordAbaRank,keywordAbaRankChangeCount,trafficShare
/openapi/v2/keywords/product-traffic-terms
- Input: same request shape as
keywords/competitor-product-keywords - Data window: daily observations surfaced through a sliding ~7-day window
- Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Key fields from live response/schema:
exploreType,absolutePosition,pageIndex,pagePosition,asin,keyword,estimateImpressionPoint,asinTotalEstimateImpressionPoint,avgPosition,daysCoverageRate,observationCount,keywordEstimateSearchCount,keywordEstimateSearchGrowthCount,keywordEstimateSearchCountChangeRate,keywordAbaRank,keywordAbaRankChangeCount,trafficShare - Live validation note: current live response item shape matches
keywords/competitor-product-keywordsfield-for-field; keep the semantic distinction in output wording rather than assuming a unique schema
/openapi/v2/keywords/product-traffic-terms-overview
- Input:
asin,date, optionalmarketplace - Data window: latest weekly overview snapshot at or before the requested date; compares all keyword impression traffic under the ASIN with the previous period
- Date rule: prefer T-1 or earlier for
date; avoid current-date lookup unless explicitly requested - Response shape:
datais an object ornull - Key fields from live localhost MCP response:
periodStartDate,periodEndDate,asin,site,organicImpressionPoint,sponsoredProductImpressionPoint,sponsoredBrandImpressionPoint,sponsoredBrandVideoImpressionPoint,sponsoredRecommendImpressionPoint,organicImpressionPointPrev,sponsoredProductImpressionPointPrev,sponsoredBrandImpressionPointPrev,sponsoredBrandVideoImpressionPointPrev,sponsoredRecommendImpressionPointPrev,first3PagesNewOrganicKeywords,first3PagesLostOrganicKeywords *Prevfields are previous-period baselines for the matching current impression-point fieldsfirst3PagesNewOrganicKeywordsandfirst3PagesLostOrganicKeywordsare arrays of objects withkeyword,pageIndex, andpagePositionfirst3PagesNewOrganicKeywordslists keywords newly entering ORG first three pages;first3PagesLostOrganicKeywordslists keywords that dropped out of ORG first three pages- Live validation request: MCP tool
openapi_v2_product_traffic_terms_overviewonhttp://localhost:8080/mcp,asin="B01CGLCGRA",date="2026-06-29",marketplace="US"
/openapi/v2/keywords/product-traffic-terms-timeline
- Input:
asin, exactkeyword,dateFrom,dateTo, optionalmarketplace,page,pageSize,sortBy,sortOrder - Data window: ASIN + keyword timeline across the requested date range; date range cannot exceed 60 days
- Date rule: prefer T-1 or earlier for
dateTo; avoid current-date lookup unless explicitly requested - Response shape:
datais an array - Metric groups:
keyword*fields are keyword traffic-forecast dependency data for the provided keyword's corresponding metric period, indicated bykeywordPeriodStartDate/keywordPeriodEndDatelatest*fields are the ASIN's latest product/listing/rank snapshot on the specifieddate- impression-point fields,
avg*fields, ad-activity fields, and placement observations are rolling metrics for the most recent 7 days ending at the givendate
- Diagnosis curves/events: price (
latestPrice), BSR (latestSmallCategoryBsr,latestBigCategoryBsr), sales (latestMonthlySaleCnt), rating (latestRatingAmt,latestRatingCnt), traffic estimate (impression-point fields plusavgOrganicObservation/avgAdObservation), and listing events (latestTitle,latestMainImageLink) - Key fields from live localhost MCP response:
date,site,asin,keyword, listing snapshot fields such aslatestTitle,latestPrice,latestCurrency,latestLink,latestMainImageLink,latestBrandName,latestMonthlySaleCnt,latestRatingAmt,latestRatingCnt,latestSmallCategoryName,latestSmallCategoryBsr,latestBigCategoryName,latestBigCategoryBsr,latestProductHasVideo; placement fields such asexploreTypes,exploreRecommendTypes,organicImpressionPoint,sponsoredProductImpressionPoint,sponsoredBrandImpressionPoint,sponsoredBrandVideoImpressionPoint,sponsoredRecommendImpressionPoint,latestOrganicPosition,latestOrganicPageIndex,latestOrganicPagePosition,latestOrganicObservedAt,latestAdPosition,latestAdPageIndex,latestAdPagePosition,latestAdObservedAt,avgOrganicObservation,avgAdObservation; keyword snapshot fields such askeywordPeriodStartDate,keywordPeriodEndDate,keywordEstimateSearchCnt,keywordEstimateSearchGrowthCnt,keywordAbaRank,keywordAbaRankGrowthCnt,keywordAbaTopClickShareRate,keywordAbaTopConversionShareRate,keywordTitleDensity,keywordTotalSkuCnt,keywordObservedSkuCnt,keywordOrganicSkuCnt,keywordSponsoredProductSkuCnt,keywordSponsoredBrandSkuCnt,keywordSponsoredBrandVideoSkuCnt,keywordSponsoredRecommendSkuCnt; ad activity fieldsadActiveObservationCount,adActiveDayCoverageRate,adCampaignCnt,adCnt - Live validation request: MCP tool
openapi_v2_product_traffic_terms_timelineonhttp://localhost:8080/mcp,asin="B01CGLCGRA",keyword="yoga mat",dateFrom="2026-06-23",dateTo="2026-06-29",marketplace="US"
Local Review Toolkit
When /reviews/analysis lacks aggregation (ASIN has <50 reviews or no daily snapshot),
fall back to live raw reviews + your own LLM. The toolkit does NOT call any external
LLM — you (the calling skill's LLM) perform the Map/Reduce steps.
Workflow:
# 1. Fetch raw reviews (up to 100, cursor-paginated, ~60s, 10 credits at full)
zoodata.py reviews-raw --asin B0XXXXXXXX [--marketplace US] [--max-pages 10]
# 2. For EACH review, render the per-review Map prompt
zoodata.py review-tag-prompt --review '<single review JSON>' \
[--product-title "..."] [--product-category "..."]
# → Your LLM produces a JSON object with sentiment + 11 dimension arrays
# (mentioned_scenarios, mentioned_issues, mentioned_positives, mentioned_improvements,
# mentioned_buying_factors, mentioned_pain_points, user_profiles, mentioned_usage_times,
# mentioned_usage_locations, mentioned_behaviors, keywords)
# Suggested map parallelism: ~20 concurrent if your LLM supports it
# 3. Collect candidate phrases per dimension. For EACH dimension render the Reduce prompt
zoodata.py review-reduce-prompt --label-type positives \
--candidates '["comfortable","comfy","very comfortable",...]'
# → Your LLM produces {clusters: [{canonical, members}, ...]}
# Suggested chunk size for `keywords` dim when >150 candidates: 150 per call
# 4. Aggregate into reviews/analysis-compatible consumerInsights
zoodata.py review-aggregate --reviews raw.json --tagged tags.json --clusters clusters.json
# → Output shape matches /reviews/analysis: reviewCount, avgRating,
# sentimentDistribution, consumerInsights[], topKeywords[]
When to use the toolkit instead of reviews/analysis:
- ASIN has fewer than 50 reviews
reviews/analysisreturns sparseconsumerInsights(missing dimensions)- Need the freshest possible data (Spider scrape vs. T+1 BigQuery snapshot)
- Need to analyze a brand-new product that has no daily snapshot yet
Field Differences Across Endpoints
| Data | markets | products/competitors | realtime/product | reviews/analysis | realtime/reviews | price-band | brand | history |
|---|---|---|---|---|---|---|---|---|
| Sales | sampleAvgMonthlySales | monthlySalesFloor | ❌ | ❌ | ❌ | sampleSalesRate | sampleGroupMonthlySales | monthlySalesFloor[] |
| Price | sampleAvgPrice | price | buyboxWinner.price | ❌ | ❌ | bandMin/MaxPrice | sampleAvgPrice | price[] |
| BSR | sampleAvgBsr | bsr (int) | bestsellersRank[] | ❌ | ❌ | ❌ | ❌ | bsr[] |
| Rating | sampleAvgRating | rating | rating | avgRating | rating (per review) | sampleAvgRating | sampleAvgRating | rating[] |
| Reviews | sampleAvgReviewCount | ratingCount | ratingCount | reviewCount | reviews[] (raw text, max 100) | ❌ | sampleAvgRatingCount | ratingCount[] |
| Insights | ❌ | ❌ | ❌ | ✅ consumerInsights | ❌ (raw only — feeds Local Review Toolkit) | ❌ | ❌ | ❌ |
| Concentration | topSalesRate | ❌ | ❌ | ❌ | ❌ | sampleTop3BrandSalesRate | CR10 | ❌ |
| Opportunity | ❌ | ❌ | ❌ | ❌ | ❌ | sampleOpportunityIndex | ❌ | ❌ |
Confidence Labels (all skills)
- 📊 Data-backed — direct API data
- 🔍 Inferred — logical reasoning from data
- 💡 Directional — suggestions, predictions
Strategy recommendations and subjective conclusions are NEVER 📊. Extreme growth (>200%) = 💡 only.
Data Notes
- Sales (
monthlySalesFloor) = lower-bound estimate - Realtime = live; products/competitors = ~T+1 delay
- Amazon US only (amazon.com) — more marketplaces planned
- Each call consumes credits; check
meta.creditsConsumed
Links
Reviews
No reviews yet. Be the first.
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