Skip to main content
Glama
CONN-SKILL

@connskill/mcp-growth-services

Official

site

Purchase 30-day cookieless web analytics for a domain, including tracking snippet, read-only dashboard link, and stats API; hosted in Germany for 0.5 USDC on Base via x402.

Instructions

Buy cookieless website analytics for 30 days: snippet, read-only dashboard link and stats API, hosted in Germany (paid) (costs 0.5 USDC on Base via x402)

Input Schema

NameRequiredDescriptionDefault
nameNoDisplay name (optional)
domainYesHostname of the site to track, e.g. shop.example.com
confirmNewPurchaseNoSet true only to intentionally buy an identical completed request again. Never use for retries or accepted/unclear purchases.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and handles the important non-obvious traits well: it is a paid, one-off purchase costing 0.5 USDC on Base via x402, hosted in Germany (a data-residency signal relevant to analytics), and it lists exactly what the buyer receives. What is missing is the irreversibility/refund picture of the charge and any auth prerequisites.

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?

A single front-loaded sentence that puts the verb, the product and the term first, then qualifications. The trailing stack of parentheticals — '(paid) (costs 0.5 USDC on Base via x402)' — is slightly redundant since 'paid' and the explicit price say the same thing, but it is compact overall.

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 a paid provisioning tool with no annotations and no output schema, the description covers what is bought, for how long, where it is hosted, what it costs, and which deliverables come back. It lacks only failure/refund semantics and auth requirements, which is a modest gap for this complexity.

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 description coverage is 100%, including a detailed warning on confirmNewPurchase about intentional repurchase vs retries, so the schema already does the heavy lifting. The description adds nothing about any of the three parameters, 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?

The description names a concrete action (buy) and resource (cookieless website analytics for 30 days) and enumerates the deliverables: snippet, read-only dashboard link, stats API. That makes it distinguishable from siblings like site_stats (read stats) or site_renew (renew). It stops short of explicitly naming those siblings, and the bare tool name 'site' does no work on its own.

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 only implied: the word 'Buy' and the 30-day term suggest this is for provisioning a new subscription rather than reading or renewing. There is no explicit when-to-use, no exclusion, and no pointer to site_renew for existing sites or site_stats for retrieving data, which are the obvious alternatives in the sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.