decode_url
Decode URL-encoded text by converting percent-encoded characters to their original representation.
Instructions
URL decode text
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | URL encoded text to decode |
Decode URL-encoded text by converting percent-encoded characters to their original representation.
URL decode text
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | URL encoded text to decode |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint: false, but the description does not add behavioral context (e.g., that decoding is a pure transformation, no side effects). Without contradiction, a score of 3 reflects minimal added value.
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 extremely concise (three words) with no fluff. However, it is so minimal that it barely provides more than the tool name; slightly more structure could improve readability.
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 simple tool with one parameter and no output schema, the description paired with the schema provides all necessary information. The tool's purpose and parameter are fully covered.
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 well-described parameter. The description adds no additional meaning beyond what the schema already provides ('URL encoded text to decode'), so baseline 3 applies.
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 'URL decode text' clearly states the action (decode) and the resource (URL encoded text). It is specific and distinguishes from sibling tools like decode_base64 or decode_html.
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?
No guidance on when to use this tool versus alternatives such as decode_html or decode_base64. The description only states what it does without contextual usage hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/wrenchpilot/it-tools-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server