Save hours every week. This ppt reply tool 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 bears the full disclosure burden, yet it says nothing about what the tool produces, whether it mutates state, what inputs it expects, or any limits. The only behavioral claim ('works in any LLM chatbot') is promotional and uninformative.
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?
The definition is short, but brevity here comes from omission rather than economy: the lead sentence is a benefit claim ('Save hours every week') and the second is marketing positioning, so no sentence carries operational information.
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 no explanation of the output or of the lone optional parameter, the definition leaves an agent unable to predict what invoking this tool will do. For a tool with a completely empty required-parameter set, the description needed to explain the default behavior and delivers nothing.
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?
With a single optional parameter at 100% schema description coverage, the schema already explains 'query' as scoping the analysis. The description adds no meaning beyond this, so the baseline of 3 applies despite the generally poor text.
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 text merely restates the tool name ('this ppt reply tool toolkit') and then describes 'a battle-tested prompt and operating playbook for restaurant/brand growth,' which gives no verb+resource statement of what a PPT reply action does. That framing is actively misleading for a ppt-* tool and offers nothing to distinguish it from the ten-plus ppt-* siblings.
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?
There is no when-to-use guidance, no exclusion criteria, and no mention of any alternative among the many ppt-audit/ppt-gen/ppt-polish/ppt-rewrite siblings. 'No setup, works in any LLM chatbot' is an availability claim, not usage direction.
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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