Launchelion

Get AI tool detail

get_tool

Read-onlyIdempotent

Fetch the full public detail for one AI tool by its listing slug (as returned by search_tools' toolUrl, e.g. '/tools/acme-writer' -> slug 'acme-writer'). Call this after search_tools to get a tool's full description, launch date, revenue signals (verified or self-reported), and for-sale status. Returns null if the slug doesn't resolve to a live Launchelion listing.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes	The tool's listing slug.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`tool`	Yes	null when the slug does not resolve to a live listing on this site.

TDQS

A5/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds critical behavioral context: the null return for non-resolving slugs and the nature of data (verified or self-reported revenue signals). No contradictions found.

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 includes an example and edge-case note without redundancy. Every sentence earns its place; no fluff.

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 an output schema present, the description need not explain return structure, but it covers all key aspects: purpose, usage sequence, data content, and null behavior. It is complete for a simple read-only fetch tool.

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

Parameters5/5

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

The description adds substantial meaning beyond the schema's minimal 'The tool's listing slug' by illustrating the exact format and transformation from toolUrl to slug (e.g., '/tools/acme-writer' -> 'acme-writer'). This is highly valuable for correct invocation.

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 verb 'Fetch' and specific resource 'full public detail for one AI tool by its listing slug'. It distinguishes from siblings by explicitly referencing search_tools and listing what data is returned (description, launch date, revenue signals, for-sale status). The purpose is unambiguous.

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

Usage Guidelines5/5

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

Gives explicit usage instruction: 'Call this after search_tools to get a tool's full description...' and explains the slug derivation from toolUrl. It sets expectations for null return, which guides when to use. This clearly frames the tool's role relative to alternatives.

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

A4.7/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: searching listings, retrieving listing details, finding alternatives, viewing purchasable add-ons, creating a checkout, and submitting a tool. There is no meaningful overlap between any two tools, even though search and alternatives both relate to discovery, their inputs and outputs are clearly separated.

Naming Consistency5/5

All six tool names follow a consistent verb_noun snake_case pattern: create_checkout, get_tool, list_alternatives, list_offers, search_tools, submit_tool. The verb is always first and the resource focus is clear, making the toolset predictable and easy to navigate.

Tool Count5/5

Six tools is a well-scoped size for the server's purpose: discovering, retrieving, comparing, submitting, and optionally promoting AI tool listings. Each tool earns its place and there is no bloat or thinness.

Completeness5/5

The toolset covers the full public-facing lifecycle of the domain: search and discovery, detail retrieval, alternative lookup, submission of new tools, and monetization via offers and checkout. There are no obvious dead ends; the only intentionally external step is the human completing checkout, which is clearly documented.

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