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amazon-product-research-mcp

asin_profit_calc

Read-only

Estimate whether an ASIN can hit a target profit margin given current buybox price, estimated FBA fees, and Amazon referral fee. Use when the user asks 'can I make money on this ASIN', 'profit calculator', 'margin estimate for B08N5WRWNW', 'is this ASIN profitable to sell', or any margin/profit question. Also returns product brand, title, price (or price range) and fulfillment (FBA/FBM/AMZ + amz/fba pct) for the ASIN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesASIN to analyze (e.g. B08N5WRWNW).
cogsNoYour cost of goods in USD. If omitted, the tool estimates breakeven COGS.
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
target_margin_pctNoTarget profit margin percentage (default 20).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that the tool consumes buybox/FBA/referral data and returns brand, title, price/price range, and fulfillment details. This is coherent with the read-only hint and provides useful context beyond the annotations.

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 compact sentences. The first front-loads purpose and usage triggers; the second lists additional return fields, which is justified because there is no output schema. No fluff or repetition.

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

Completeness4/5

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

The tool is simple and the schema covers all parameters. The description also reveals return contents (brand, title, price/price range, fulfillment with percentages), which compensates for the missing output schema. It could be more explicit about the exact shape of the profit-estimate result, but this is not critical.

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?

All four parameters already have schema descriptions (100% coverage), so the description is not required to add parameter-level detail. It does contextualize the calculation (buybox price, FBA fees, referral fee), but it does not add semantics beyond what the schema already provides for cogs, marketplace_id, or target_margin_pct.

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 opens with a specific verb+resource: 'Estimate whether an ASIN can hit a target profit margin' and lists the inputs used (buybox price, FBA fees, referral fee). The trigger-phrase list further disambiguates it from other ASIN-level tools such as asin_buybox_history or asin_comparables.

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?

It provides explicit user-phrase triggers ('can I make money on this ASIN', 'profit calculator', 'margin estimate for B08N5WRWNW', 'is this ASIN profitable to sell') and generalizes to 'any margin/profit question'. It does not, however, name alternative tools or state when not to use it, so it stops short of a full 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.