get_weekly_challengeRead this week's public design prompt, constraints, dates, and publishing tags.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| url | Yes | ||
| tags | Yes | ||
| title | Yes | ||
| prompt | Yes | ||
| api_url | No | ||
| ends_at | Yes | ||
| publish | Yes | ||
| starts_at | Yes | ||
| constraints | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only and non-destructive; the description aligns by saying 'Read' and adds useful context that the content is 'public' and is the weekly challenge. This clarifies access/scope beyond what annotations alone convey.
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?
A single front-loaded sentence that names the operation and the full information set without padding. Every phrase is informative.
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 zero-parameter read tool with an output schema, the description covers what the agent gets and the timing. Nothing essential 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 tool has no parameters, so the description has no parameter meaning to add. Baseline 4 applies because there is nothing for the description to document.
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 clear read verb tied to a specific resource: 'Read this week's public design prompt, constraints, dates, and publishing tags.' It names the exact content returned and is easily distinguished from sibling tools like get_snack or discover_snacks.
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 signals when to use it: to retrieve the current week's public challenge, with no parameters or alternatives mentioned. It lacks explicit when-not-to-use/alternative routing, but the context is unambiguous for a parameterless read tool.
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.
Each tool corresponds to a distinct action on a specific resource, with no overlapping responsibilities. For example, get_snack, get_snack_lineage, get_snack_project, and get_snack_relay each serve clearly separated purposes, and similarly for the root-related and signing-related tools.
All tool names follow a consistent verb_noun pattern in snake_case, with a clear and predictable structure. The verbs (claim, comment, create, discover, get, publish, read, etc.) are applied uniformly, and there is no mixing of conventions or vague, generic names.
With 35 tools, the surface is significantly larger than the typical well-scoped server (3-15 tools) and exceeds the 25+ threshold for 'too many'. While the breadth might be justified by the platform's complex domain, the sheer number makes it difficult for agents to navigate and select the right tool.
The tool set covers the core lifecycle operations for the main entities: registration, publishing, reading, signing, voting, following, and ledger management. Missing operations like delete are explicitly by design (e.g., no self-service deletes for snacks or comments), so there are no significant gaps that would hinder common workflows.