list_industries
List the industries Kettle Logic publishes guidance for (name + slug) as JSON.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
mcp-kettlelogic
TDQS
A4.5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, description fully discloses behavior: a read-only listing returning JSON with name and slug. No side effects or permissions implied. Complete transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 13 words, contains all necessary information. Perfectly concise with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers input (none), output format (JSON with name and slug), and purpose. Output schema exists and description aligns. Complete for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters so baseline is 4. Description adds no parameter info, which is appropriate since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action (List), resource (industries), and output format (name+slug as JSON). Distinguishes from siblings like get_industry_overview which provides more detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when/why to use this tool vs alternatives. However, given zero parameters and simple purpose, usage is self-evident. Could mention that this is the entry point for getting available industries before using other 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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TDQS
A3.8/5.0
Disambiguation5/5
Each tool has a distinct purpose: fetching a single article, fetching an industry overview, listing articles, listing industries, and searching articles. There is no overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_article, list_industries), making them predictable and easy to understand.
Tool Count5/5
With exactly 5 tools, the set is well-scoped for the server's purpose of retrieving and searching article and industry content. No tool feels extraneous or missing.
Completeness5/5
The tool set covers all likely operations for a read-only content API: listing and getting both articles and industries, plus search. There are no obvious gaps for the stated domain.