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Top Launches

top_launches
Read-onlyIdempotent

Get today's and recent top Product Hunt launches — new product and startup launches. Use this to see what launched today/recently or which products are trending. Returns name, tagline, vote/comment counts, URLs, and topics. Example: top_launches({ first: 10, order: "RANKING" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
firstNoNumber of launches to return (default 10, max 20)
orderNoSort order: "RANKING" (default — trending), "VOTES" (most upvoted), or "NEWEST" (most recently launched)
_apiKeyNoOptional — your own Product Hunt developer token for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "first": 10,
      -    "order": "RANKING"
      -  },
      -  {
      -    "_apiKey": "your-producthunt-api-key",
      -    "first": 5,
      -    "order": "VOTES"
      -  }
      -]New value: +[
      +  {
      +    "first": 10,
      +    "order": "RANKING"
      +  },
      +  {
      +    "first": 5,
      +    "order": "VOTES"
      +  }
      +]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "first": 10,
      +    "order": "RANKING"
      +  },
      +  {
      +    "_apiKey": "your-producthunt-api-key",
      +    "first": 5,
      +    "order": "VOTES"
      +  }
      +]
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnly, openWorld, idempotent, and non-destructive behavior, so the description only needs to add context. It adds temporal scope ('today's and recent'), the trending aspect, and the return payload details such as name, tagline, counts, URLs, and topics.

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?

Three short, useful elements are front-loaded: what is returned, when to use it, and a call example. There is no filler or tautology.

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 no output schema, the description supplies the key return fields, while the input schema supplies defaults and enum values. An agent has enough information to call the tool correctly.

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

Parameters3/5

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

Schema coverage is 100% and the schema fully explains first, order, and _apiKey, so the baseline applies. The description's example mirrors the schema example and does not add parameter meaning beyond what is already structured.

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: 'Get today's and recent top Product Hunt launches.' It also states the domain and the returned fields, which makes it distinguishable from the broad sibling set such as get_post and pipeworx_trending.

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 says when to use it: 'Use this to see what launched today/recently or which products are trending.' It does not name an alternative or an exclusion case, so it stops short of perfect routing guidance.

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

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