x402-dad-joke
Dad Joke: Fetch a random dad joke from icanhazdadjoke.com. No input needed; returns the joke text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Dad Joke: Fetch a random dad joke from icanhazdadjoke.com. No input needed; returns the joke text.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well: 'fetch from icanhazdadjoke.com' reveals the external network dependency, 'random' discloses non-determinism, and 'returns the joke text' states the output shape. Minor gaps remain—no mention of failure modes, rate limits, or whether output is raw text versus a JSON payload—but these are minor for such a simple tool.
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 every clause earns its place: source, randomness, no-input requirement, and return content. The only waste is the leading 'Dad Joke:' label, which duplicates the tool name x402-dad-joke.
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 tool with no output schema and no annotations, the description covers the essentials: what it fetches, from where, that no input is needed, and what it returns. The only omissions—precise response format and error behavior—are low-stakes for a trivial fetch tool.
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 has zero parameters and 100% schema description coverage, so per the rubric the baseline is 4. The description's 'No input needed' reinforces the empty schema and confirms the caller should pass nothing, which is the only parameter-related information an agent needs.
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 ('Fetch') and a specific resource ('a random dad joke from icanhazdadjoke.com'), clearly stating the tool's function. The genre qualifier 'dad joke' and the named source domain help an agent distinguish it from generic joke tools like x402-random-joke, though it stops short of explicitly differentiating itself from siblings.
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?
Usage context is implied by the tool's singular purpose and the source domain, but there is no explicit guidance about when to use this versus alternatives such as x402-random-joke, x402-chuck-norris, or x402-advice-slip. No exclusions or when-not-to-use conditions are given.
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.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.