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sanhao-global-experts

review-rescue-agent

Turn expertise into output. This review rescue agent 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

C2.3/5.0
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 and does not meet it. It claims the pack "includes the complete prompt, usage guide, and edge-case handling" but never says what the tool actually returns, whether it produces a single prompt or a bundle, whether the response is static content or generated analysis, or whether the optional query changes behavior.

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?

It is short and front-loaded, but the opening line ("Turn expertise into output") and the "in minutes" claim are pure promotion that occupies the most valuable position. The one factually useful sentence about included materials 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 must explain return shape and invocation behavior, and it does not. For a tool whose whole value proposition is the content it emits, leaving the output entirely unspecified is a substantive gap.

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 parameter with 100% schema description coverage, so the schema already explains that the query scopes the analysis. The description adds no further meaning about what scoping accomplishes, which matches the baseline 3 for well-covered schemas.

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 text reads as marketing copy rather than a statement of what the tool does. "Turn expertise into output" and "helps restaurant and brand teams produce professional results" name no concrete verb or resource, and nothing distinguishes this from the many review-* siblings such as review-reply-tool or review-audit-tool. Only the phrase "prompt pack" hints that it returns prompt material, and that is inferred from a sales claim rather than stated as purpose.

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?

It gives a loose audience ("restaurant and brand teams") but no when-to-use condition, no when-not-to-use, and no named alternative among the crowded review-* family. An agent has no basis for choosing this over review-reply-tool, review-polish-tool, or review-management.

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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