[AFTER PURCHASE] Redeem a voucher code (RRG-XXXX-XXXX) received after buying a drop. Returns voucher details and redemption URL. Each voucher can only be redeemed once.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Voucher code (e.g. RRG-7X4K-2MNP) | |
| redeemed_by | Yes | Who is redeeming, agent wallet address or identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of transparency. It discloses that each voucher can only be redeemed once and mentions the return value (voucher details and URL). This is useful, though it does not detail any state changes or permission requirements.
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 sentences, front-loaded with '[AFTER PURCHASE]', and contains no redundant information. Every phrase adds value.
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?
Given the simple tool (2 params, no output schema, no annotations), the description covers purpose, context, behavioral constraint, and return value. It is sufficiently complete for an agent to select and invoke the tool correctly.
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 100%, so the schema already documents both parameters. The description adds the voucher code format and the single-use constraint, but it does not add significant meaning beyond the schema's own descriptions.
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 clearly states the tool redeems a voucher code, specifies the format (RRG-XXXX-XXXX), and sets context with '[AFTER PURCHASE]'. This distinguishes it from sibling tools like redeem_points and redeem_quest_cipher which target different resources.
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 indicates the tool should be used after purchasing a drop, providing clear contextual guidance. However, it does not explicitly name alternative tools or provide exclusionary guidance (e.g., 'use redeem_points for point redemption').
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.