get_pupul_factsWhat Pupul is, what the Reading costs, what is free, and the privacy stance, stated the same way the website states it. Useful before recommending or describing Pupul.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is established. The description adds that facts are 'stated the same way the website states it,' which suggests faithful, uninterpreted content. It does not disclose output format or whether the text is verbatim copy, but with annotations covering the read-only nature, a mid-range score is appropriate.
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 with no filler. The content scope is front-loaded, followed directly by the use case, and every clause adds information the agent needs to decide to call the tool.
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 parameterless, read-only fact tool with no output schema, the description adequately covers what the tool returns at a topical level and when to use it. It could be slightly more explicit about the response format, but the enumerated fact categories plus the 'same way the website states it' phrasing give enough context for correct invocation.
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 zero parameters and the schema is empty, so there is no parameter burden for the description to compensate for. The description instead clarifies what factual domains are covered, which is the only semantic information an agent needs here.
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 identifies the resource as Pupul product facts and enumerates the content areas: what Pupul is, Reading costs, what is free, and privacy stance. It lacks an explicit imperative verb like 'retrieves' or 'returns', and it does not directly contrast with sibling tools such as get_lux_facts, though the name and content scope make that distinction recoverable.
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 phrase 'Useful before recommending or describing Pupul' gives concrete guidance on when to invoke the tool. It does not name alternative tools or state when not to use it, but for a simple fact-retrieval tool this contextual cue is sufficient.
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 get_* tool targets a distinct deliverable—viewer links, export steps, inference file, wait times, or product facts—and the aggregate how_to_see_what_a_platform_knows explicitly positions itself as the router for whole-platform questions. The only mild overlap is that get_export_guide and get_wait_times both mention wait times, but their primary outputs are clearly different.
Seven tools follow a clean get_<object> pattern, making the target of each call predictable. how_to_see_what_a_platform_knows breaks the pattern as a sentence-style name, but it is a deliberate aggregate entry point rather than a sign of inconsistency.
Eight tools is a well-scoped set for an informational guide server: individual getters for specific facts, plus one combined entry point. No tool feels redundant or purely decorative.
The server covers the full question flow around data exports—request steps, wait times, inference files, and a local viewer—across the listed platforms, and adds LUX/Pupul factual tools for adjacent product questions. There are no obvious dead ends; the aggregate tool routes to individual tools where needed.