gf.gcc_opportunity_scoreUnit economics, ROI and GCC opportunity score. Price: 0.75 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| currency | No | ||
| landed_cost | Yes | ||
| referralCode | No | ||
| delivery_days | No | ||
| payment_fee_pct | No | ||
| competitor_count | No | ||
| fulfillment_cost | No | ||
| paymentSignature | No | ||
| ad_cost_per_order | No | ||
| expected_sale_price | Yes | ||
| marketplace_fee_pct | No | ||
| returns_reserve_pct | No | ||
| other_cost_per_order | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It does disclose the cost (0.75 USDC) and payment mechanism (x402), which is useful context. However, it does not state whether the call is read-only, what side effects occur, whether paymentSignature is required, or what the response contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, with the core concept first and the pricing detail in a separate sentence. It contains no filler words, though it could be more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 13-parameter paid tool with no annotations and no output schema, the description omits parameter guidance, return value expectations, and usage context. It is enough to hint at what the tool returns, but not enough for an agent to confidently decide to call it or prepare a correct request.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% for 13 parameters, and the description does not explain any of them beyond the general phrase 'unit economics, ROI.' Required fields like landed_cost and expected_sale_price are not semantically expanded, and no units, percentage conventions, or input relationships are provided. This is insufficient for an agent to correctly populate the many optional parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the subject (GCC opportunity score) and hints at the inputs (unit economics, ROI), but it lacks a verb such as 'calculates' or 'returns' and does not differentiate this tool from siblings like gf.gcc_product_decision or gf.gcc_merchant_pack. It is a partial purpose statement rather than a clearly defined operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. Sibling tools such as gf.free_profit_check and gf.gcc_product_decision exist, but the description provides no selection criteria, prerequisites, or exclusions. The pricing line is payment context, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools overlap in purpose, particularly among the GCC analysis services (free_profit_check, gcc_opportunity_score, gcc_product_decision) and the status reporting tools (agent_commerce_status, payment_status, settlement_status, universal_status). While descriptions clarify differences, an agent may struggle to choose between these related services without careful reading.
All tools use the 'gf.' prefix and snake_case, providing a consistent base. However, the pattern mixes noun_phrases (agent_budget, payment_status) with verb-based names (execute, quote) and adjective_noun combinations (free_profit_check), making the naming somewhat inconsistent in style though still readable.
At 18 tools, the count is slightly above the typical 15-tool sweet spot but remains reasonable for a comprehensive commerce gateway server that covers discovery, quoting, payment, status, and analytics. The scope justifies the number without feeling bloated.
The tool surface covers the main lifecycle: discovering capabilities, obtaining quotes, executing transactions, checking payment and settlement status, monitoring provider health, and reviewing metrics. Minor gaps exist (no explicit refund/cancel or merchant account creation), but these are not critical to the core workflows.