Save hours every week. This resume tpl 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 provided, so the description carries the full behavioral burden, yet it discloses nothing about what is returned, whether it is read-only, whether it consumes quota, or how long the prompt is. The only concrete claims ('no setup', 'works in any LLM chatbot') are promotional and unverifiable.
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?
Two sentences of hype with no front-loaded statement of function. The space is spent on benefits ('Save hours', 'No setup') rather than on the information an agent needs to select and call the tool correctly.
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?
The tool has one param, no output schema, and no annotations, so the description must explain both what comes back and how to use the returned template. Instead it offers generic advertising, leaving the central question, what the tool produces and how it should be applied, unanswered.
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 'query' parameter with 100% schema description coverage, so the schema already explains, minimally, that it scopes the analysis. The description adds nothing beyond that, which is the baseline expectation when schema coverage is complete.
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 never states a specific verb and resource. It says the toolkit 'gives you a battle-tested prompt and operating playbook for restaurant/brand growth', which hints at returning a prompt template, but that is buried in sales copy and conflicts with the tool name 'resume-tpl-tool'. An agent cannot confidently tell what this tool actually does or how it differs from the many other *-tpl-tool 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?
'Save hours every week' and 'No setup, works in any LLM chatbot' are marketing claims, not usage guidance. There is no statement of when to call this tool, when not to, or which sibling template tool to prefer, despite a large set of similarly named template tools.
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.