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viridis-agent-fleet

viridis-agent-fleet

by jdhart81
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

subscriptions__subscription_status

Check subscription status and current-period quota for B2B monthly seats. Returns lifecycle, entitlement, and overage information with masked account key.

Instructions

[subscriptions — B2B monthly seats, entitlement quota, overage, and MRR] Return bearer-owned subscription lifecycle and current-period quota. The account key is always masked in output.

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": {
      "account_id": "<account_id>"
    },
    "name": "subscriptions__subscription_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
account_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.11
    • addedInput schema / properties / account_id / title
      Added value: +"Account Id"
    • addedInput schema / title
      Added value: +"subscription_statusArguments"
  2. Changed2 schema fields changedv0.1.9
    • removedInput schema / properties / account_id / title
      Removed value: -"Account Id"
    • removedInput schema / title
      Removed value: -"subscription_statusArguments"
  3. Added

TDQS

C2.7/5.0
Behavior2/5

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

No annotations provided, so the description carries the full burden. It mentions output masking (account key masked) but does not disclose whether the operation is read-only, required permissions, or any side effects. The verb 'Return' implies read access but is not explicit.

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?

The description is efficient with two sentences, but the first sentence includes a bracketed domain label that may be considered clutter. Overall, it is front-loaded and reasonably concise.

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

Completeness2/5

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

For a tool returning complex data (subscription lifecycle, quota), the description is vague. No output schema exists, and the description does not clarify what fields or structure to expect, leaving agents with incomplete understanding.

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 0%. The description does not elaborate on the sole parameter 'account_id' beyond its existence, leaving agents without guidance on format, source, or constraints.

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 clearly states the tool returns subscription lifecycle and current-period quota for a bearer-owned subscription. While the name is clear, the description includes a domain header that might be extraneous but does not hinder understanding.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like subscriptions__mrr_summary or subscriptions__usage_summary. There are no explicit usage conditions, prerequisites, or exclusions.

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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