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sanhao-global-experts

weekly-reply-tool

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use weekly reply tool 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

C2.2/5.0
Behavior2/5

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

With zero annotations, the description carries the full behavioral burden, and it discloses almost nothing: no indication of side effects, permissions, persistence, or what a call actually produces. The only hint is that the output "ships as a full prompt kit with step-by-step instructions," which weakly gestures at a return format but is framed as a product deliverable rather than tool behavior.

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 nearly all of the text is pitch material — "AI-powered," "instantly," "no prompt engineering needed," "30-day support promise" — none of which helps an agent decide or call. The genuinely useful information (what the tool produces) is buried and under-specified rather than front-loaded.

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?

A single-parameter tool with no annotations and no output schema should at minimum explain what the generated weekly reply artifact contains and how it differs from neighboring weekly-* tools. Instead the description reads as a storefront listing, leaving the agent unable to predict the result or confirm the tool is the right one.

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 already documented in the schema, so baseline 3 applies. The description adds no additional meaning about how the query scopes the weekly reply output, but it is not required to compensate given full schema coverage.

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

Purpose2/5

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

The description restates the name with marketing framing ("generate a ready-to-use weekly reply tool workflow") without stating a concrete verb+resource an agent can act on. "AI-powered restaurant & brand intelligence pack" describes a product bundle, not an operation, and it does nothing to distinguish this from the dozens of weekly-* siblings (weekly-write-tool, weekly-gen-tool, weekly-reply-tool variants, etc.).

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 directive, no exclusions, and no mention of any alternative despite a crowded weekly-* and reply-* sibling family. "No prompt engineering needed" and the 30-day support promise are sales copy, not invocation guidance, so an agent has no basis for choosing this tool over weekly-write-tool or review-reply-tool.

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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