YAML-JSON Converter
yaml-jsonConvert between YAML and JSON formats.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | YAML or JSON string to convert | |
| direction | No | Conversion direction | auto |
yaml-jsonConvert between YAML and JSON formats.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes | YAML or JSON string to convert | |
| direction | No | Conversion direction | auto |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / properties / directionAdded value: +{
+ "default": "auto",
+ "description": "Conversion direction",
+ "enum": [
+ "yaml-to-json",
+ "json-to-yaml",
+ "auto"
+ ],
+ "type": "string"
+}Input schema / properties / inputAdded value: +{
+ "description": "YAML or JSON string to convert",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "input"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the conversion and does not mention auto-detection behavior (despite the 'auto' direction default in the schema), error handling, output format, or edge cases like invalid input. This is a significant gap for a conversion tool.
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 description is a single, direct sentence with no filler. It is appropriately front-loaded and conveys the core functionality instantly. There is no wasted text.
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?
For a tool with no annotations and no output schema, the description is too sparse. It does not explain the expected return format, auto-detection behavior, or error handling. While the tool is simple, the description fails to provide enough context for an agent to understand nuances such as the 'auto' direction or what happens with invalid input.
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?
The input schema provides 100% coverage for both parameters: 'input' described as 'YAML or JSON string to convert' and 'direction' with an enum and default. The description adds no additional meaning beyond what the schema already explains, meeting the baseline for high schema coverage.
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 clearly states the tool's function: 'Convert between YAML and JSON formats.' The verb 'convert' plus the resource 'YAML and JSON' leaves no ambiguity. It also distinguishes from sibling tools like xml-json-converter and json-to-csv by specifying the exact formats involved.
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?
The description implies usage (when you need to convert YAML to JSON or vice versa) but does not explicitly state when to prefer this tool over alternatives such as format-converter or other converter tools. There are no exclusions or conditions provided.
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.
Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.
Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.
202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.
The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.