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sanhao-global-experts

store-opening-checklist

Turn expertise into output. This store opening checklist prompt pack helps restaurant and brand teams produce professional results in minutes. Includes the complete prompt, usage guide, and edge-case handling.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2/5.0
Behavior2/5

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

No annotations exist, so the description carries the full behavioral burden, and it discloses almost nothing: it does not say whether the call is a read or a generation, what form the response takes, or whether anything is persisted. 'Includes the complete prompt, usage guide, and edge-case handling' only vaguely hints at output content while remaining unclear about the actual 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?

Only three sentences, but the opening line ('Turn expertise into output') and the time-promise clause are pure filler that take the prime front-loaded position. The one potentially informative sentence about pack contents is buried at the end.

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 annotations and no output schema, the description is the only source of behavioral information, and it leaves the return shape, the mutation profile, and the choice versus siblings entirely unexplained. For a pack/checklist generator in a crowded store-launch family, this is far from sufficient.

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?

The single optional 'query' parameter has 100% schema description coverage, so the schema already defines it. The description adds no semantics about how the query scopes the generated pack, so the baseline 3 for full schema coverage applies.

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 is predominantly marketing copy ('Turn expertise into output', 'produce professional results in minutes') that restates the name rather than stating what the tool actually returns or does. It never says whether it emits a prompt, a checklist template, or a generated document, so an agent cannot distinguish it from siblings like restaurant-newstore-launch or shop-open-prep.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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 tool. The audience phrase 'restaurant and brand teams' is the only scoping signal and it does not help an agent choose between this and the many neighboring store-launch 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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