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llm-toolkit

llm-toolkit

by 0x1Jar
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Encode

encode

Encode data using methods like URL, double URL, hex, base64, HTML entity, or unicode encoding.

Instructions

Encode data using various methods (url, doubleUrl, hex, base64, htmlEntity, unicode)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "data": "<data>",
      "method": "<method>"
    },
    "name": "encode"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataYes
methodYes
variantNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavior. It states the action but omits important traits like error handling, output format, or side effects (e.g., is it safe? destructive?). The minimal text leaves the agent guessing about invocation behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded with the core purpose. It efficiently communicates the tool's role, though it could include more detail without becoming verbose. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given three parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, behavior across methods, or constraints like valid input formats. A more complete description is needed for accurate tool usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description should explain parameters. It mentions the 'method' enum implicitly by listing values but does not describe 'data' or the optional 'variant' parameter at all. The schema provides enums, but the description adds no additional meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action (encode data) and lists the supported methods, making it easy to understand its core function. However, it does not explicitly distinguish from the sibling 'decode' tool, but the naming and description suffice.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'jwt-encode' or 'decode'. There is no mention of prerequisites or context for choosing methods, leaving the agent without decision support.

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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