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JavaScript
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producthunt_makers

Fetch makers for a Product Hunt product by slug, including names, usernames, headlines, avatars, follower counts, and pagination via cursor.

Instructions

Retrieve Product Hunt product makers. Lists the makers of a Product Hunt product, looked up by its slug in id. Each maker has a name, username, headline, avatar, follower count and the posts they made. The response includes total_count and claim status, and the returned end_cursor can be passed as cursor for the next page.

Input Schema

NameRequiredDescriptionDefault
idYesProduct Hunt slug
cursorNoPagination cursor

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
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 does a fair job: it enumerates returned maker fields (name, username, headline, avatar, follower count, posts), notes total_count and claim status, and explains pagination via end_cursor -> cursor. It doesn't state auth/permission needs, but the read-only listing behavior is clear.

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?

Front-loaded with the core action, then return shape, then pagination. Three tight sentences with no filler, though the field enumeration is slightly listy.

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?

No output schema exists, so the description must cover returns, and it does: maker fields, total_count, claim status, and the pagination mechanism. An agent has everything needed to call it and interpret the response.

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?

Schema coverage is 100%, so baseline is 3; the description adds real value by explaining that `id` is a product slug and that the previous response's `end_cursor` should be passed as `cursor`, which the schema does not say.

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?

States a specific verb+resource: 'Lists the makers of a Product Hunt product, looked up by its slug in `id`.' This distinguishes it from nearby siblings like producthunt_customers and producthunt_product, though it never names them explicitly.

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?

The lookup key (`id` = product slug) implies the usage context, but there is no explicit when-to-use guidance, no exclusions, and no routing to alternatives such as producthunt_customers or producthunt_product.

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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