Lanzamientos IA

List paid add-ons (offers)

list_offers

Read-onlyIdempotent

List the optional paid add-ons a maker can buy to promote their listing (name, one-sentence effect, price in USD). Listing is always free; these only ADD reach and are always labeled 'Sponsored'. Call this to see what's purchasable before create_checkout. During free early access (early-bird), offers are not yet purchasable and this says so (purchasable=false).

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`note`	Yes
`site`	Yes
`offers`	Yes
`purchasable`	Yes	False during free early access — nothing can be bought.

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds meaningful behavior: listing is free, add-ons only increase reach, results are always labeled 'Sponsored', and during early access offers are marked purchasable=false. This gives the agent important business-context and edge-case knowledge that annotations alone do not convey.

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 three sentences and front-loaded with the core purpose. Every sentence earns its place: product definition, business context, usage guidance, and an early-access caveat. There is no filler or repetition of schema/annotation information.

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?

For a zero-parameter, read-only list tool with an output schema, the description is complete. It names the returned fields, clarifies the economic model, connects to checkout, and exposes the early-access behavior. No important context appears 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 tool has zero parameters and the input schema is empty, so there is nothing for the description to explain. With 0 params, the baseline is 4, and the description appropriately focuses on output semantics rather than parameter details.

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 opens with a specific verb and resource: 'List the optional paid add-ons a maker can buy to promote their listing.' It clearly distinguishes these purchasable add-ons from the always-free listing and from the sibling create_checkout tool, so the tool's purpose is unambiguous.

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?

The description gives clear context with 'Call this to see what's purchasable before create_checkout,' explicitly situating it in the purchase workflow. It does not list exclusions or alternatives, but this sequencing guidance is enough for an agent to know when to invoke it.

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

All Lanzamientos IA tools Inspect

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

A4.7/5.0

Disambiguation5/5

Each tool targets a distinct action: searching, retrieving details, listing alternatives, listing offers, creating a checkout, and submitting a new tool. Descriptions clearly differentiate search_tools from list_alternatives (free-text vs. named competitor) and get_tool (specific slug lookup), so an agent can reliably choose the right one.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (create_checkout, get_tool, list_alternatives, list_offers, search_tools, submit_tool). The verbs are distinct and meaningful, making the API highly predictable.

Tool Count5/5

Six tools is well-scoped for a server that handles discovery, submission, and paid promotion for AI tool listings. Each tool serves a clear purpose without redundancy, and the count feels appropriate for the domain's complexity.

Completeness5/5

The tool surface covers the primary user journeys: finding tools (search_tools), examining a specific tool (get_tool), comparing alternatives (list_alternatives), understanding promotional offers (list_offers), purchasing an offer (create_checkout), and adding new tools (submit_tool). There are no obvious dead ends, and the workflow from discovery to purchase to submission is fully supported.

Resources

Need Help?