Save hours every week. This sph listicle kit toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Optional user query to scope the analysis. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden, and it discloses almost nothing: it does not say whether invoking it returns a prompt template, a filled-in listicle draft, or instructions, nor whether it has side effects. 'Save hours every week' and 'no setup' are benefit claims, not behavioral facts an agent can act on.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, but the lead sentence is pure advertising ('Save hours every week') rather than a front-loaded statement of function, and 'listicle kit toolkit' is redundant. Almost none of the text earns its place as selection guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 truth for an agent, and it omits the return shape, the platform assumptions behind 'sph', and any prerequisite or limitation. For a prompt-kit tool that is otherwise trivially simple, this still leaves too much unknown to invoke it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is a single optional parameter with 100% schema description coverage, so the schema already explains that 'query' scopes the analysis; baseline 3 applies. The description adds nothing about how the query influences the generated playbook 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.
Does the description clearly state what the tool does and how it differs from similar tools?
"sph listicle kit toolkit gives you a battle-tested prompt and operating playbook" mostly restates the tool name with marketing framing rather than stating a concrete verb+resource. It never explains what an 'sph listicle' is, what the playbook contains, or how it differs from the dozens of sibling sph-*-kit tools (sph-column-kit, sph-roundup-kit, sph-review-kit).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage guidance is 'No setup, works in any LLM chatbot', which describes portability rather than when to choose this tool. There is no when-to-use condition, no mention of the target scenario beyond a vague 'restaurant/brand growth', and no routing to or away from the sibling kit 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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