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sanhao-global-experts

product-pick-master

A production-ready product pick master 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?

No annotations are provided, so the description must carry the full behavioral burden. It mentions delivery as a "copy-paste prompt pack with examples," which hints at the return artifact, but it does not state whether the tool generates or retrieves the pack, how the optional query affects output, or what side effects or permissions are involved.

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?

The description is short and front-loads the audience and deliverable, but it contains marketing filler such as "production-ready" and "you can run today" that does not help an agent invoke the tool correctly. The two sentences are efficient enough but not maximally clear.

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?

With no output schema and no annotations, the description should explain what calling the tool returns and how the query scopes the workflow. It only says the result is a prompt pack with examples, leaving the output format, workflow steps, and query behavior unspecified. This is inadequate for a tool whose main value is a structured deliverable.

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 one optional query parameter with 100% schema description coverage, so the schema already explains its meaning. The description adds no additional semantics for the query, but with full schema coverage the baseline score of 3 is appropriate.

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 says this is a "product pick master system" that delivers a "structured, repeatable workflow" as a "copy-paste prompt pack with examples," but it never specifies the concrete operation or what "product pick" means. It also does not differentiate the tool from the many similar prompt-pack or workflow siblings. The purpose is inferable but vague.

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?

The only usage context is the target audience: "marketing and operations leaders." There is no guidance on when to use this tool, when not to use it, or which sibling tool to choose instead. An agent would have to guess from the name and surrounding tool list.

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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