Save hours every week. This sph quote 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 disclosure burden, yet it never says what the tool actually returns (a prompt template? a playbook document?) or whether it performs any analysis. 'No setup' is the only behavioral detail, which is far short of what an unannotated tool needs.
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?
Only three short sentences, but they are front-loaded with a benefit hook ('Save hours every week') instead of the tool's function, and the middle sentence mixes two unrelated framings (quote kit vs. restaurant/brand growth). Most of the text is promotional rather than informative.
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, no output schema, and a vague name, the description is the only source of truth and it leaves the core question unanswered: what does an agent get back and for what content domain. The 'restaurant/brand growth' framing also sits oddly against an 'sph' (WeChat Channels) quote kit, adding ambiguity rather than clarity.
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?
Schema description 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 beyond the schema — it never mentions how the query influences the returned prompt or playbook.
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?
The description leans on sales copy ('Save hours every week', 'battle-tested prompt and operating playbook') rather than stating a concrete verb and resource. 'sph quote kit toolkit' merely restates the name, and the claim about 'restaurant/brand growth' does not tell an agent what this specific kit produces or how it differs from the dozens of sibling sph-*-kit tools.
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?
No guidance on when to invoke this versus sph-adcopy-kit, sph-topic-kit, sph-script-kit or the other ~30 sibling kits, and no prerequisites or exclusions. 'Works in any LLM chatbot' is an environment claim, not a usage rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.