Launchelion

Submit a new AI tool

submit_tool

Submit a new AI tool to Launchelion on behalf of its maker. Creates a draft listing (not yet public) and returns a claimUrl the maker must visit to sign up and claim/publish it. Call this only when a user explicitly wants to list their own tool — never to submit a tool on someone else's behalf without their email. Rate-limited globally to 5 submissions per hour. Supply tagline, problemSolved, logoUrl and imageUrls whenever you can: they are what make the published listing look like a real product page rather than a stub.

Input Schema

TableJSON Schema

Name	Required	Description
`url`	Yes	The tool's https homepage URL.
`name`	Yes	The tool's name.
`email`	Yes	The maker's email — used to claim the listing on signup.
`logoUrl`	No	https URL of the tool's logo. We copy it to our own storage — we never hotlink the maker's host.
`tagline`	No	One line shown on every card (max 60 chars). Supply it — without one we fall back to a truncated description.
`xHandle`	No	X/Twitter handle, without the @.
`category`	Yes	Category slug, e.g. 'agents', 'writing', 'coding', 'design', 'marketing', 'productivity', 'video', 'analytics'.
`imageUrls`	No	Up to 5 https screenshot URLs, best first. Copied to our own storage. Without any, the listing shows a generated placeholder card instead of a real screenshot.
`description`	Yes	A description of the tool (40-1000 chars).
`problemSolved`	No	What problem the tool solves, in the maker's words (max 160 chars). Rendered as its own block on the listing page.
`xHandleIsFounder`	No	True when the handle is the founder's personal account rather than the product's.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes
`error`	No
`claimUrl`	No	Where the maker signs up to claim the DRAFT. Present only when ok is true.

TDQS

A4.9/5.0

Behavior5/5

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

Despite annotations being all false, the description adds substantial behavioral detail: the listing is a draft (not public), requires maker signup via claimUrl, has a global rate limit, and image files are copied to Launchelion's storage. These are not in annotations, so the description carries the burden well.

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?

Five sentences, each packed with relevant information. The main purpose is front-loaded, followed by usage constraints, rate limit, and parameter advice. No redundant wording or 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?

For a tool with 11 parameters, 5 required, and an output schema, the description covers the essential context: what the tool does, when to use it, constraints, and tips on filling parameters. The output schema presumably details the return fields, so the description doesn't need to.

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?

The input schema has 100% description coverage, so the baseline is 3. The description adds extra guidance by highlighting which optional parameters matter most ('Supply tagline, problemSolved, logoUrl and imageUrls whenever you can') and explains their impact (makes listing look like a real product page). This goes slightly beyond the schema.

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 action ('Submit a new AI tool'), the resource ('to Launchelion'), and the outcome ('creates a draft listing... returns a claimUrl'). It also distinguishes from siblings by mentioning the claim process, which is unique to this tool compared to get_tool or search_tools.

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?

Explicitly states when to call: 'only when a user explicitly wants to list their own tool.' It also gives a negative constraint: 'never to submit a tool on someone else's behalf without their email,' which provides clear usage boundaries. The rate limit also sets expectations on frequency.

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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