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amazon-product-research-mcp

risk_assessment

Read-only

Risk + protection assessment for an ASIN or brand. Returns composite risk score (0-100), recent MAP violation events (≤10, each with the offending ASIN's product brand, title, price or price range and fulfillment FBA/FBM/Amazon), unauthorized seller list (≤10), and 1-3 recommended actions. Use for 'flag risk events on my brand' or 'is this ASIN risky?' style prompts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinNo
daysNoLookback window for MAP events. Default 30.
brandNo
kind_inNoComma-separated flagged-event kinds to keep (e.g. map_violations,amazon_dominated).
max_countNo
max_priceNo
min_countNo
min_priceNo
severity_inNoComma-separated severities to keep (high/medium/low).
buybox_sellerNoExact offending buy-box seller (case-insensitive).
event_date_toNo
product_brandNoExact product brand (case-insensitive).
fulfillment_inNoComma-separated FBA/FBM/AMZ to keep.
marketplace_idNo1 = Amazon UK, 2 = Amazon US (default), 4 = Amazon CA, 5 = Amazon AU, 6 = Amazon DE, 7 = Amazon JP, 8 = Amazon IT, 9 = Amazon FR, 10 = Amazon ES, 11 = Amazon MX, 12 = Amazon BR
event_date_fromNoYYYY-MM-DD.
max_listed_priceNo
min_listed_priceNo
buybox_seller_containsNo
product_brand_containsNo
product_title_containsNo
max_fulfillment_amz_dom_pctNo
max_fulfillment_fba_pen_pctNo
min_fulfillment_amz_dom_pctNo
min_fulfillment_fba_pen_pctNo

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the return structure in useful detail: composite risk score range, up to 10 MAP events with specific per-event fields, up to 10 unauthorized sellers, and 1–3 recommended actions. This is strong behavioral transparency, especially with no output schema to rely on.

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?

Two tight sentences: the first packs purpose and output details, the second adds concrete trigger phrasing. No fluff, front-loaded, every clause earns its place.

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

Completeness3/5

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

The description covers purpose, output shape, and usage prompts, which is valuable given the missing output schema. However, with 24 optional parameters and only 33% schema coverage, it leaves significant ambiguity about which inputs are central (e.g., asin vs. brand) and how the filters affect results. Adequate but with clear gaps.

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

Parameters2/5

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

Schema description coverage is only 33%, and the description does not compensate. It only says "for an ASIN or brand," which loosely maps to the `asin` and `brand` parameters, but the 20+ filter parameters (prices, fulfillment, counts, date ranges, severities) are not explained anywhere in the description. The agent gets little help understanding which parameters matter or how they combine.

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?

The description clearly states the tool performs risk and protection assessment for an ASIN or brand, then enumerates concrete outputs: a risk score, MAP violation events, unauthorized seller list, and recommended actions. It differentiates from sibling tools like map_violations_today and unauthorized_sellers by presenting a synthesized composite assessment, and the trigger-phrase examples reinforce intent.

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

Usage Guidelines4/5

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

The description gives explicit usage guidance: "Use for 'flag risk events on my brand' or 'is this ASIN risky?' style prompts." This tells an agent when to invoke the tool, though it does not explicitly name alternatives or state when *not* to use it, so it falls just short of a 5.

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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TDQS

A3.5/5.0
Disambiguation2/5

The tool set is extremely granular, with multiple clusters that overlap in purpose (e.g., amazon_search_results/search_products/shopping_search; watchlist_delta/watchlist_diff; find_undercompeted_brands/category_undercompeted_brands; operator_new_brands/operator_new_on_brand). Although descriptions are detailed, the boundaries between many 'find opportunity' and 'watchlist change' tools are subtle enough that an agent could easily misselect.

Naming Consistency4/5

The vast majority follow a verb_noun snake_case convention with clear prefixes (asin_, brand_, category_, operator_, watchlist_, playbook_, find_, top_). A few noun-style exceptions (competitive_landscape, risk_assessment, brand_under_attack, buybox_loss_alert) break the pattern, but they are minor and do not obscure the overall scheme.

Tool Count1/5

With 82 tools, the server is far beyond the 50+ extreme threshold. Even though the domain is broad, many tools are highly granular variants (e.g., filter_brands_by_fba_share vs filter_operators_by_fba_share; watchlist_delta vs watchlist_diff) that could be merged or parameterized, imposing a heavy cognitive and context burden on agents.

Completeness5/5

The surface is extraordinarily complete for Amazon product research: discovery, ASIN/brand/category analytics, buybox and BSR history, sourcing evaluation, risk/MAP monitoring, watchlists, playbooks, operator intelligence, cross-marketplace checks, and live refreshes. Workflows like authorized_seller_set → buybox_loss_alert and watchlist_add → watchlist_delta are fully supported, with no obvious dead ends.