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submit_project

Suggest a product for the directory. The submission is saved as pending and reviewed by a person; nothing is published automatically.

Input Schema

NameRequiredDescriptionDefault
urlYesOfficial website or app-store URL.
nameYes
tagsNo
contactNoOptional private email.
why_tryYesWhat a user can do with the free option.
categoryYes
logo_urlNoOptional public URL of a square logo (PNG, JPG, WebP or GIF, up to 2 MB). Resized to 256x256; fetch failures never reject the submission.
one_linerYes
agent_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / category / enum
      Previous value: -[
      -  "utilities",
      -  "productivity",
      -  "developer",
      -  "education",
      -  "sports",
      -  "environment",
      -  "ai-agents"
      -]New value: +[
      +  "ai-agents",
      +  "developer",
      +  "design-media",
      +  "productivity",
      +  "business",
      +  "finance",
      +  "games",
      +  "education",
      +  "health",
      +  "utilities"
      +]
  2. Changed1 schema field changed
    • addedInput schema / properties / logo_url
      Added value: +{
      +  "description": "Optional public URL of a square logo (PNG, JPG, WebP or GIF, up to 2 MB). Resized to 256x256; fetch failures never reject the submission.",
      +  "type": "string"
      +}
  3. First observed

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations at all, the description carries the full burden and does disclose the key post-condition: the submission is stored as pending, human-reviewed, and never auto-published. That is meaningful lifecycle context an agent cannot get elsewhere. It stops short of covering failure handling, duplicate rejection, or what identifier is returned.

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 short sentences, front-loaded with the action and immediately followed by the review/pending constraint. Nothing is redundant or padded.

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

Completeness3/5

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

For a 9-parameter mutation tool with no output schema and no annotations, the description covers only the review lifecycle. It omits what the caller gets back (submission ID/status), field expectations for the five required parameters, and duplicate-handling behavior, leaving real gaps.

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

Parameters2/5

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

Schema description coverage is only 44%, so the description needs to compensate, but it says nothing about any of the 9 parameters. Undocumented fields such as name, one_liner, tags, category, and agent_name rely entirely on bare schema types; the description adds zero meaning beyond structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Suggest a product for the directory.' That is clearly a write/submission action, which separates it from the read-oriented siblings (get_project, search_projects, list_categories). It does not explicitly name a sibling to disambiguate against, keeping it below a 5.

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

Usage Guidelines3/5

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

The description implies the use case (proposing a new product) but gives no explicit guidance on when to prefer this over siblings, no prerequisite such as checking for duplicates with search_projects first, and no exclusions. Usage is inferred rather than stated.

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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