[PLAY] Discover an easter egg from get_world_eggs and reveal its film. For a gated egg, pass your answer to the challenge; open eggs need none. The first discovery banks the reward to your wallet. Returns the video URL. Eggs are content, not listings: there is nothing to buy.
| Name | Required | Description | Default |
|---|---|---|---|
| answer | No | Answer to the challenge (gated eggs only) | |
| egg_slug | Yes | Egg slug from get_world_eggs | |
| agent_wallet | Yes | Your agent wallet address on Base |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals key traits: 'The first discovery banks the reward to your wallet,' 'Returns the video URL,' and 'there is nothing to buy.' It does not mention failure modes or what happens on repeat discoveries, but the 'first discovery' phrasing implies the reward is one-time. This is solid but not exhaustive.
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 four sentences, front-loads the primary purpose, and each sentence adds value: prerequisite, gating logic, reward behavior, and return value. There is no fluff or redundancy, making it appropriately sized and well-structured.
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 tool's moderate complexity and lack of output schema/annotations, the description covers the essential facets: what it does, source of input, gated vs. open handling, reward condition, return value, and a clarifying statement that it is not a purchase. It omits potential edge cases like undiscovered egg failures, but overall it is complete enough for an agent to use 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%, with each parameter already described in the schema. The description largely repeats this information (e.g., 'egg_slug from get_world_eggs', 'answer for gated eggs'), adding little extra meaning beyond reinforcing the schema. Baseline 3 is appropriate since the schema does the heavy lifting.
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 action (discover), the resource (easter egg from get_world_eggs), and the outcome (reveal its film). It also distinguishes this from listing tools and purchase tools by saying 'Eggs are content, not listings: there is nothing to buy.' This specificity differentiates it from siblings like get_world_eggs and initiate_purchase.
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?
The description implies the prerequisite (use egg_slug from get_world_eggs) and provides conditional guidance for gated vs. open eggs. It also includes an exclusion ('nothing to buy') to prevent misuse. However, it does not explicitly name when not to use the tool or mention alternative tools, 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.
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.