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producthunt_search

Search Product Hunt for products, users, or launches by keyword, with filters for type, page, featured status, and topics.

Instructions

Search for products, users, or launches on Product Hunt. Searches Product Hunt for the required query. type is product (default), user or launch, and page starts at 1. featured and topics apply to launch search only. Results come as edges with pageInfo and pagesCount; launch search also returns topic aggregations.

Input Schema

NameRequiredDescriptionDefault
pageNoPage number (1-based)
typeNoResult type: **product** (default), **user**, or **launch**
queryYesSearch keywords
topicsNoLaunch search only: comma-separated topic slugs
featuredNoLaunch search only: featured launches only

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / type / enum
      Added value: +[
+  "product",
+  "user",
+  "launch"
+]
  2. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose the response shape ('edges' with 'pageInfo' and 'pagesCount', plus topic aggregations for launch search) and the 1-based paging convention. It omits auth requirements, rate limits, and result caps, but the output structure disclosure is meaningful given no output schema exists.

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

Conciseness4/5

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

Information is front-loaded and dense: purpose, then query, then type/page, then type-specific params, then return shape. There is mild redundancy between the first sentence and 'Searches Product Hunt for the required query', but no filler.

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

Completeness4/5

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

For a five-parameter search tool with no output schema and no annotations, the description covers purpose, parameter scoping by type, pagination, and the response envelope. Missing only peripheral details like auth or rate limits, which are minor for a public search endpoint.

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 description coverage is 100%, so all five parameters are already documented in the schema, including the 'launch search only' notes on topics/featured. The description largely restates these (default type, page starts at 1) and adds little syntax or format detail beyond the schema, so the baseline 3 applies.

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

Purpose4/5

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

The description names a specific verb and resource ('Search for products, users, or launches on Product Hunt') and enumerates the three result types, so the agent knows the scope. It does not name or contrast with siblings such as producthunt_product or producthunt_launches, so differentiation is partial.

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

Usage Guidelines3/5

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

It implicitly signals when certain parameters apply ('featured and topics apply to launch search only') but never states when to choose this tool over the entity-specific siblings (producthunt_product, producthunt_launches, producthunt_makers). Usage is inferable but not explicit.

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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