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Pangolinfo Amazon Data MCP

by Pangolin-spg
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TypeScript
Remote

list_bestsellers

Get top 50 Best Sellers rankings for an Amazon category with 24-hour rank changes to benchmark leaders, spot new entrants, and set niche baselines.

Instructions

[Amazon Best Sellers] Top-50 ranking for a category with 24h rank deltas. Use when: user says "X category bestsellers" / "who's #1 in X" / "any new entrants climbing" / "benchmark top sellers"; setting baseline products during niche scouting; tracking category leadership in competitor radars. Don't use: for new arrivals (use list_new_releases); for full category listings beyond top 50 (use list_category_products); when you only have a keyword (use search_categories first). Returns: data.json[0].data.{ reftag, recsList } — recsList is a JSON-string array (parse twice); each row { id, metadataMap.{ render.zg.rank, currentSalesRank, percentageChange, twentyFourHourOldSalesRank } }. Pair with: ↑ categorySlug from user or scene inference (e.g. 'electronics' / 'home-garden' / 'beauty'); ↓ feed id (ASIN) into get_amazon_product for single-product deep-dive. Cost: ~1 point/call, ~5s. Tips: categorySlug is the hyphenated English slug in amazon.com/Best-Sellers URL paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteNoAmazon marketplace. Defaults to amz_us.amz_us
formatNoResponse format. Defaults to 'json' — structured Top-50 ranked ASIN list. Use 'markdown' for the rendered page text.json
zipcodeNoZIP code that must match the site country (amz_us → US zip, amz_jp → JP zip, ...). Optional; backend picks a random one from the per-country pool when omitted. Cross-country zips (e.g. amz_us + JP zip) are rejected by the backend. Examples: 10001 (NY) / 90001 (LA) / 100-0001 (Tokyo).
categorySlugYesAmazon Best Sellers category slug (lowercase, hyphenated). Examples: 'electronics', 'home-garden', 'beauty', 'toys-and-games'. Find these in the URL path on amazon.com/Best-Sellers.
clientSourceNo调用来源标记。仅由 Pangolinfo Skill 传 skill；普通 MCP 调用省略即可。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does well: it discloses cost (~1 point/call), latency (~5s), and the double-parse quirk of recsList being a JSON string. It does not cover error behavior, auth requirements, or rate ceilings, so it falls short of fully self-sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Labeled sections (Use when / Don't use / Returns / Pair with / Cost / Tips) are front-loaded and scannable. Despite its length, every block carries distinct operational information — there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates by unpacking the exact return path (data.json[0].data.{reftag, recsList}) and row fields. For a 5-param, annotation-free tool this is complete enough to call correctly on the first attempt.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the slug format, site enum, and zipcode constraints are already documented in the schema. The description adds the downstream pairing tip (feed ASIN into get_amazon_product), which is useful but modest added value over structured data.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource+scope: 'Top-50 ranking for a category with 24h rank deltas.' It also names the sibling tools it is not (list_new_releases, list_category_products, search_categories), so an agent can distinguish it without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'Use when' triggers quote real user phrasings ('who's #1 in X', 'any new entrants climbing') and a 'Don't use' block names three alternatives with the condition that selects each. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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