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sanhao-global-experts

flow-audit-tool

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use flow audit 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?

No annotations are supplied, so the description carries the full burden and largely fails it. It does not state whether the tool performs an analysis, returns a static prompt kit, or emits generated text; it does not say whether it is read-only or has side effects, nor what a caller receives back. The only behavioral hint — that it "ships as a full prompt kit with step-by-step instructions" — reads as product packaging copy rather than a description of runtime 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?

At three short sentences it is not bloated, but most of the wording is promotional filler — "instantly," "no prompt engineering needed," "30-day support promise" — that consumes the entire space without conveying capability. The front-loaded sentence is spent on positioning rather than on what the tool does.

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 structurally simple (one optional parameter, no annotations, no output schema), so a short description could suffice — but this one never clarifies the actual operation or returned artifact, which is exactly what the description must supply here. Given the dense sibling namespace and the absent structured metadata, an agent cannot confidently invoke it.

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% for the single optional "query" parameter, so the schema already explains its purpose. The description adds nothing about how the query scopes the analysis or what effect omitting it has, so the baseline 3 applies rather than anything higher.

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 core phrase "generate a ready-to-use flow audit tool workflow" essentially restates the tool name, with "generate" as a vague verb and no concrete resource or output named. It never distinguishes this tool from the many near-identical siblings (flow-gen-tool, flow-check-tool, flow-write-tool, flow-tpl-tool, flow-summary-tool). The opening "AI-powered restaurant & brand intelligence pack" signals a domain, but not what the tool itself does.

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 prerequisites, and no mention of any alternative among the nine other flow-* siblings. "No prompt engineering needed" and "30-day support promise" are sales claims, not selection criteria. An agent has no basis for choosing this over flow-gen-tool or flow-check-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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