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sanhao-global-experts

car-buy-advisor

A production-ready car buy advisor system for marketing and operations leaders. Get a structured, repeatable workflow you can run today - delivered as a copy-paste prompt pack with examples.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations supplied, the description carries the full behavioral burden, yet it discloses almost nothing: no indication of response length, whether it fabricates advice versus returning a template pack, or any execution constraints. The only behavioral hint is that output is a 'prompt pack with examples', which is thin for an unannotated tool.

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

Conciseness3/5

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

Two sentences with no padding, but a large share of the text is promotional filler ('production-ready', 'repeatable workflow you can run today') rather than information an agent can act on. The one substantive detail (prompt pack with examples) is buried second.

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?

The tool is simple (one optional parameter, no output schema), so modest detail would suffice, but key questions remain unanswered: what the returned pack contains, whether it is generic or tailored to the query, and why a car-buying tool targets marketing/ops leaders. For a tool whose entire value is the shape of its output, that gap matters.

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?

There is a single optional parameter ('query') with 100% schema description coverage, so the schema already documents it. The description adds no guidance on what a scoping query should contain or how it alters the returned pack, so the baseline 3 applies.

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

Purpose3/5

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

The description names the artifact ('car buy advisor system' delivered as a 'copy-paste prompt pack with examples'), which hints at the deliverable, but the verb is never stated and the stated audience ('marketing and operations leaders') is misaligned with a car-buying topic, muddying actual purpose. It also does no work to distinguish itself from buy-decision siblings such as appliance-buy-guide, big-purchase-decision, or insurance-buy-guide.

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?

There is no statement of when to invoke this tool, when not to, or which sibling to prefer for a car/vehicle purchase decision. 'You can run today' is marketing phrasing, not usage guidance.

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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