Skip to main content
Glama

Pupul data export guides

by com.noctaracorp

Get export wait times, for one platform or for all of them

get_wait_times
Read-only

How long a platform’s personal data export takes from request to ready, plus the download window and the limit the platform itself states. Pass a platform to get only that platform’s rows, which is what you want when answering one question; omit it for all 17 rows across 11 platforms. Every row comes back with a permanent id and a citation URL of the form https://pupulcorp.com/data/wait-times#, so a single fact can be cited without citing the whole table. Every figure is labeled reported (from the platform’s own help text, with source) or measured (our own request and ready timestamps, both printed). Source page: https://pupulcorp.com/data/wait-times, CC BY 4.0.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformNoOptional. Return only this platform’s rows. Omit for the whole table. Aliases resolve: twitter, meta, google takeout, youtube.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, and the description goes well beyond that by disclosing the return shape: permanent id, citation URL, and reported vs. measured labels. It also provides the source page and license, giving the agent confidence about provenance and reusability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately long but every sentence carries distinct value: primary output, parameter behavior, citation mechanism, data provenance, and source. Information is front-loaded with the core definition before optional behaviors.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With only one optional parameter and no output schema, the description carries the full burden of explaining what the agent will receive. It covers the returned fields, filtering behavior, provenance labeling, citation URLs, and source licensing — nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents the optional platform parameter with alias examples, so coverage is high. The description adds meaning by tying the parameter to the query intent ('which is what you want when answering one question') and quantifying the full result set (17 rows across 11 platforms), which helps the agent reason about cardinality.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource — export wait times — and what it measures: time from request to ready, download window, and platform-stated limit. It also distinguishes the optional platform filter from the full-table behavior, making the tool's role clear relative to its siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly tells the agent when to pass a platform ('when answering one question') and when to omit it ('for all 17 rows across 11 platforms'). It does not explicitly compare against alternatives like get_export_guide, but the context for using this tool is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Pupul data export guides toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness5/5

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.

Resources