Save hours every week. This labor contract check 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: permissions, whether input is analyzed or merely a static playbook is returned, and limits are all absent. The one genuine disclosure is that the deliverable is a prompt/playbook usable in any chatbot, but that is about packaging rather than runtime behavior.
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?
It is short but front-loaded with marketing ("Save hours every week") and closes with an irrelevant deployment claim ("works in any LLM chatbot"). The one informative phrase is buried in the middle, so the structure wastes its limited space.
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 is simple (one optional param, no output schema), but the description never says what a labor contract check produces or what standards it applies, and the restaurant/brand-growth framing actively misdirects. For a zero-annotation tool, this is not enough to call it correctly.
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 coverage is 100% with a single optional 'query' parameter already documented, so baseline is 3. The description adds no meaning about how the query scopes the analysis or what form it should take.
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 largely restates the name ("labor contract check toolkit") and then muddles the picture by pitching "restaurant/brand growth," which does not describe a contract-checking operation. An agent learns only that the tool returns a "prompt and operating playbook," not what it actually validates in a labor contract. The many sibling check/gen/polish tools mean this vague framing gives no basis for selection.
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 prerequisites, and no mention of any alternative among the numerous contract-* siblings (contract-check-tool, contract-audit-tool, contract-review family, etc.). The only situational claim is sales copy about saving time.
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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