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submit_tool

Submit an AI tool to PPToGo's free AI tools directory (pptogo.com/tools) on behalf of its maker. The listing is reviewed by the PPToGo team (typically 2-3 business days); the decision is emailed to contact_email, and once approved it is live at listing_url. One listing per product website — a duplicate returns tool_already_listed with the existing slug. Free listing only; no featured placement is sold through this tool.

Input Schema

NameRequiredDescriptionDefault
nameYesTool name, e.g. "Magic Hour"
has_apiNoHas a public API
categoryYesDirectory category
logo_urlNoOptional public logo URL (SVG or PNG)
website_urlYesProduct homepage, https://…
has_human_uiNoHas a web / desktop app people use directly
contact_emailYesMaker's email for the review decision
pricing_modelNoOptional pricing model
has_mcp_serverNoHas an MCP server
long_descriptionNoOptional detail-page copy in Markdown: what it does, who it is for, links to docs / MCP / API
short_descriptionYesOne sentence shown on the directory card (max 280 chars)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint=false, idempotentHint=false, destructiveHint=false) by disclosing the asynchronous review flow (2-3 business days), where the decision is delivered (contact_email), where the result appears (listing_url), and the duplicate-submission error path. This is exactly the mutation-behavior context annotations cannot carry.

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?

Three dense sentences with the core action front-loaded and no filler; each sentence adds a distinct operational fact (process, timing, delivery, constraints).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter, 5-required submission tool with no output schema, the description covers the review lifecycle, the failure mode, and listing limits. It stops short of describing the review outcome states or re-submission after rejection, but the schema already documents every field.

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%, so the baseline is 3. The description adds modest meaning by tying contact_email to the review decision and listing_url to the live result, but it does not explain category, the boolean flags, or copy-length expectations beyond what the schema already says.

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?

States a specific verb and resource ('Submit an AI tool to PPToGo's free AI tools directory') plus the acting capacity ('on behalf of its maker'). It is clearly distinguishable from siblings such as submit_post or write_tool_review without opening any schema.

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 scopes usage well: free listing only, no featured placement sold, one listing per product website, and a duplicate returns tool_already_listed. It does not name sibling alternatives, but the explicit scope exclusions make the intended use clear.

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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