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sanhao-global-experts

dy-listicle-kit

Save hours every week. This listicle kit toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.

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 burden. It does imply the tool returns a prompt plus playbook rather than generating finished content, which is useful, but it never states whether it is a pure read/retrieval operation, what the response looks like, or how the returned playbook is meant to be applied. 'No setup, works in any LLM chatbot' is compatibility marketing rather than behavioral disclosure.

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?

It is short, but two of the three sentences ('Save hours every week,' 'No setup, works in any LLM chatbot') are advertising copy that forwards no information an agent can act on, and the marketing hook is front-loaded ahead of the actual purpose.

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?

For a single-parameter prompt-kit tool with no annotations and no output schema, the description should explain what is returned and how to use it. It leaves the agent guessing about the deliverable's shape and the platform context (Douyin), which is the one thing that distinguishes it from the surrounding family of listicle kits.

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% for the single optional 'query' parameter, so the schema already documents it. The description adds nothing about how the query scopes the returned prompt, so the baseline of 3 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 says it delivers a 'battle-tested prompt and operating playbook,' which hints at the deliverable, but never states a verb or resource such as 'returns the Douyin listicle content prompt template.' The 'dy' prefix, i.e. Douyin, is never unpacked, and the scope claim 'restaurant/brand growth' does not match a listicle-format content kit, so the agent cannot confidently tell what the tool produces versus siblings like xhs-listicle-kit or gzh-listicle-kit.

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 and no mention of alternatives. The only framing is 'for restaurant/brand growth,' which tells the user a domain but not the condition that should select this tool over the many other *-listicle-kit siblings.

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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