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sanhao-global-experts

gk-exam-system

Turn expertise into output. This exam system 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

C2.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. 'Includes the complete prompt, usage guide, and edge-case handling' hints at the returned payload, but nothing says whether the tool mutates anything, whether it just returns static prompt text, or what the response looks like — a serious gap for an opaque single-param tool.

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?

Only three short sentences, but 'Turn expertise into output' and 'in minutes' are marketing filler that earn no place ahead of the actual behavior. What remains is compact, but it is not front-loaded with the information an agent needs to act.

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?

No annotations and no output schema mean the description must explain the call's result and boundaries, and it does neither. For a tool whose name implies exam generation but whose text describes a 'prompt pack', the agent is left guessing what is produced and when to reach for 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 coverage is 100% and the single 'query' parameter is already documented as an optional scoping input, so the baseline is 3. The description adds no meaning about how the query scopes the analysis or what happens when it is omitted.

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 name says 'exam system' but the description talks about 'restaurant and brand teams' producing 'professional results in minutes' — the two never reconcile. It never states a concrete verb+resource (generate an exam? return a prompt template? retrieve a prompt pack?), so an agent cannot tell what invoking this actually does.

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, when-not-to-use, or alternative mentioned, despite many overlapping siblings (exam-planner, exam-kao-gong-pro, cert-exam-route, shiyebian-exam-guide, k12-homework-system) that an agent must choose between. The only audience hint, 'restaurant and brand teams', is not an invocation condition.

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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