[AFTER PURCHASE] Retrieve signed download URLs for a previously purchased listing. Use if you lost the original download link from confirm_purchase.
| Name | Required | Description | Default |
|---|---|---|---|
| tokenId | Yes | Token ID of the purchased listing | |
| buyerWallet | Yes | Buyer wallet used at purchase |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It correctly implies a read-only action ('Retrieve') and adds the prerequisite that the purchase must already have occurred. It does not disclose side effects (likely none) or error handling, but for this simple retrieval the context is adequate.
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 two short sentences, front-loaded with '[AFTER PURCHASE]' for immediate context, and every word adds value. There is no redundancy or padding.
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 simple two-parameter tool with no output schema or nested objects, the description fully covers what the tool does, when to use it, and how it relates to confirm_purchase. No critical information is missing.
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?
The input schema already describes both parameters with 100% coverage (e.g., 'Buyer wallet used at purchase' and 'Token ID of the purchased listing'). The tool description adds little beyond restating the purchase context, so the schema carries the explanatory weight, meriting the baseline score.
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 uses a specific verb 'Retrieve' and identifies the resource as 'signed download URLs for a previously purchased listing'. It also clearly distinguishes itself from sibling tools by mentioning confirm_purchase and the AFTER PURCHASE context, making its purpose unambiguous.
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?
It gives explicit usage guidance: 'Use if you lost the original download link from confirm_purchase.' This tells the agent exactly when to invoke this tool versus alternatives, providing a clear decision rule.
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.
Most tools have distinct purposes with clear category tags. Minor potential confusion between get_current_brief vs list_briefs and get_brand vs get_brand_mcp_endpoint, but descriptions clarify intent.
All tools follow a consistent verb_noun pattern using lowercase with underscores, e.g., check_agent_standing, list_drops, submit_design. No mixing of conventions.
32 tools is on the high side, but the server covers a wide domain including browsing, purchasing, design submission, concierge, and marketing. Each tool serves a specific function, though some consolidation could be possible.
The tool surface covers the full lifecycle of browsing, purchasing, design creation, commissions, and concierge services. Minor gaps like refund handling are absent, but the core workflows are well-supported.