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tylerbrabo98

Customer Health MCP

by tylerbrabo98

Get full account detail

get_account_details

Fetch an account's full raw billing, 90-day usage, feature adoption, and support ticket history to inspect the data behind a churn-risk score or summary.

Instructions

Fetch the complete raw record for one account: its Stripe-style billing/subscription record, its full 90-day product-usage time series and feature adoption, and its full support ticket history. Use this when you need the underlying data behind a risk score, not just the summary. Returns a clear error if the accountId does not exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountIdYesThe account's unique identifier, e.g. "acct_0007"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
usageYes
billingYes
supportYes
accountIdYes
companyNameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
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 does reasonably well: it discloses the breadth of data returned (full history and time series, implying a heavy response) and the error behavior when accountId does not exist. It does not state read-only status or any permission/rate considerations, leaving a gap for a data-heavy read tool.

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 tightly written sentences with zero filler; the verb and resource come first, followed by contents, then the routing condition, then error behavior. Every sentence earns its place.

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?

An output schema exists, so return values need not be spelled out, yet the description usefully previews the payload shape. For a single-parameter read tool with full schema coverage, nothing an agent needs to call it correctly is missing.

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% and the single accountId parameter is already documented with an example format, so the schema does the heavy lifting. The description adds only an error condition for a nonexistent accountId, which is useful but not syntax or format detail beyond the schema.

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 ('Fetch') and resource ('the complete raw record for one account'), then enumerates exactly what the record contains: billing/subscription, 90-day usage time series, and support ticket history. This lets an agent distinguish it from the summary-oriented sibling get_account_risk_summary without opening either 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?

Gives a clear selection condition: 'Use this when you need the underlying data behind a risk score, not just the summary,' which implicitly contrasts with the risk-summary sibling. It stops short of naming the alternative tool explicitly or stating any exclusions/prerequisites, so it falls just below the top band.

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