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Producthunt

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Get Post

get_post
Read-onlyIdempotent

Get full details for a single Product Hunt launch by its slug — description, makers, topics, and vote/comment counts. Use after top_launches to dig into a specific new product / startup launch. Example: get_post({ slug: "notion" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe Product Hunt post slug (e.g. "notion"), from a launch's url/slug.
_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
    • addedInput schema / examples
      Added value: +[
+  {
+    "slug": "notion"
+  },
+  {
+    "_apiKey": "your-producthunt-api-key",
+    "slug": "linear"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds that it returns full details including specific fields, and provides an example call. No contradictions with annotations.

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?

Two sentences plus an example. Front-loaded with purpose. No wasted words. Example is useful for understanding parameter usage.

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 simple get tool with 2 params, no output schema, and rich annotations, the description covers purpose, usage context, example, and return fields. It is complete and requires no additional explanation.

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 already describes both parameters. Description adds a concrete example and clarifies slug origin, but doesn't significantly enhance parameter understanding beyond what schema provides.

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?

Description clearly states 'Get full details for a single Product Hunt launch by its slug' and lists what's included: description, makers, topics, vote/comment counts. It distinguishes itself from sibling 'top_launches' by specifying this is for diving into a specific launch.

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?

Explicitly says 'Use after top_launches to dig into a specific new product / startup launch.' This provides clear context on when to use. No alternatives or when-not-to are mentioned, but the guidance is clear.

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

All Producthunt toolsInspect
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