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by com.frontstat
OverviewDiscussionsAdmin

Check a launch FrontStat tracks

check_public_launch
Read-onlyIdempotent

Look up a product launch that FrontStat already tracks: its name, its rank on this week's or this month's launch board, its visibility score (0 to 100), and whether ChatGPT, Claude and Gemini recommend it for its buyer question, with the products they name instead. Returns a link to its public FrontStat page. If FrontStat does not track the domain yet, says so and links to the free report. No token needed.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "check_public_launch"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesThe product's domain or URL, for example example.com.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world). The description adds real behavioral context: the exact fields returned, the AI-recommendation check with competing products named instead, a public page link, a graceful fallback for untracked domains, and that no token is needed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and return contents in dense, waste-free prose. Slightly long, but every clause carries information an agent would otherwise have to guess.

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?

No output schema exists, so the description carries the return-value burden and does so thoroughly: named fields, score range, AI-provider coverage, link, and untracked-domain fallback. Nothing material is missing for a single-parameter read tool.

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?

Only one parameter, and schema description coverage is 100% with the schema documenting the domain/URL format and example. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 ('look up') and resource ('a product launch that FrontStat already tracks'), then enumerates the fields returned. It is clearly distinguishable from siblings like get_visibility or who_wins_instead, though it never names them explicitly.

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?

Usage is implied by the scope (checking a launch FrontStat tracks), but there is no explicit when-to-use statement or routing to an alternative tool. The only conditional guidance describes behavior for untracked domains rather than tool selection.

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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