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sanhao-global-experts

email-check-tool

Turn expertise into output. This email check tool 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

C2.2/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden and largely fails it. Mentioning that it 'includes the complete prompt, usage guide, and edge-case handling' hints at the deliverable but says nothing about side effects, required inputs, or what the invocation actually performs.

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 short sentences, but the leading two are pure sales framing ('Turn expertise into output', 'in minutes') and the substantive content — what the tool does — is absent. Brevity here reflects under-specification rather than efficiency.

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 output schema, no annotations), so a complete description should be easy to write. Instead the definition omits the core operation entirely, leaving an agent unable to decide between this and the numerous email-* siblings.

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 a single optional 'query' parameter with 100% schema description coverage, so the schema already explains it. The description adds no meaning about how 'query' scopes the check, but the baseline of 3 applies when the schema does the work.

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 never states a concrete verb+resource operation. 'Turn expertise into output' and 'helps restaurant and brand teams produce professional results in minutes' are marketing copy that restates the name ('email check tool') without saying what is actually checked (deliverability, copy, spam score, compliance) or what comes back.

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?

No when-to-use conditions, no prerequisites, and no differentiation from the many near-identical siblings such as email-audit-tool, email-polish-tool, email-summary-tool, or email-write-tool. The only contextual hint is an audience ('restaurant and brand teams'), which does not tell an agent when to select this 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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