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extract_producthunt

Read-only

Extract recent Product Hunt launches by keyword/topic search or a PH URL. Returns name, tagline, votes, comment count, topics, and launch date per result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesSearch query or PH topic URL

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, which cover safety and open-world behavior. The description adds value by disclosing the exact return fields and the scope ('recent' launches), giving the agent a clear expectation of the tool's output. There is no contradiction with annotations, and the behavioral disclosure is sufficient for a read-only extraction tool.

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 two sentences, front-loaded with the primary action, and directly lists the returned fields. Every word earns its place; there is no redundancy or filler. It is efficiently structured and immediately comprehensible.

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 tool with one simple parameter, no output schema, and solid annotations, the description is complete: it covers the input (search/URL) and the output (specific fields). The tool's simplicity means no additional details (e.g., pagination, rate limits) are necessary for an agent to invoke it 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?

The input schema fully describes the single parameter 'url' as 'Search query or PH topic URL', and the description repeats this ('by keyword/topic search or a PH URL'). Since schema coverage is 100%, the description adds no meaningful semantics beyond the schema. Baseline of 3 is appropriate.

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 clearly states the tool's function: 'Extract recent Product Hunt launches by keyword/topic search or a PH URL.' It specifies the verb (extract), the resource (Product Hunt launches), and the output fields (name, tagline, votes, comment count, topics, launch date). This differentiates it from sibling tools that target other platforms (e.g., extract_hackernews).

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 provides clear usage context by indicating the two input modes: 'keyword/topic search or a PH URL.' This tells the agent when to use the tool (when Product Hunt data is needed) but does not explicitly mention when not to use it or compare it with alternatives. The context is clear, but exclusions are absent.

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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TDQS

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.

Naming Consistency4/5

Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.

Tool Count5/5

11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.