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sanhao-global-experts

breastfeeding-guide

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use breastfeeding guide workflow - no prompt engineering needed. Ships as a full prompt kit with step-by-step instructions and a 30-day support promise.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. It hints at the deliverable shape ('ships as a full prompt kit with step-by-step instructions'), which is useful, but says nothing about what the workflow contains, whether output is static text or generated content, cost/latency, or what the '30-day support promise' actually implies operationally.

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

Conciseness2/5

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

Three sentences, and the first is irrelevant boilerplate that actively misleads, while the third is sales copy ('30-day support promise') rather than tool information. The one useful sentence is buried in the middle instead of being front-loaded.

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

Completeness1/5

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

For a zero-annotation, no-output-schema tool with a single optional parameter, the description should explain the deliverable and selection criteria versus the lite sibling. Instead it advertises a prompt kit and offers an unrelated 'restaurant & brand' framing, leaving the agent without enough to invoke it confidently.

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% and the single optional query parameter is documented in the schema as 'Optional user query to scope the analysis.' The description adds no meaning beyond that, so the baseline of 3 applies; there is no explanation of what 'scope the analysis' changes in the output.

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 middle sentence does state a verb+resource: 'generate a ready-to-use breastfeeding guide workflow.' However, the opening sentence claims it is a 'restaurant & brand intelligence pack,' which has nothing to do with breastfeeding, and the description never distinguishes this tool from the sibling 'breastfeeding-guide-lite'. The purpose is deducible but muddied by off-topic framing.

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 when-to-use guidance, no prerequisite, and no mention of the obvious alternative ('breastfeeding-guide-lite') or of when the optional 'query' parameter should be supplied. The only usage-adjacent claim is a marketing statement ('no prompt engineering needed'), which does not help an agent decide between tools.

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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