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warungcyber_get_setup_guide

Generate Markdown setup guides and copy-paste configuration snippets to connect WarungCyber to Cursor, VS Code Continue, Cline, Chatbox, or Python and Node.js SDKs, with your API key embedded.

Instructions

Generate formatted Markdown setup guides and copy-paste configuration snippets for integrating WarungCyber into Cursor IDE, VS Code Continue, Cline, Chatbox, or Python and Node.js SDKs. Embeds the provided API key (or placeholder if omitted) directly into the code sample. Read-only operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNoWarungCyber API key to embed in the configuration snippet
clientYesTarget client application or development environment

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.2
    • changedInput schema / properties / apiKey / description
      Previous value: -"Your WarungCyber API key to embed in snippet"New value: +"WarungCyber API key to embed in the configuration snippet"
    • changedInput schema / properties / client / description
      Previous value: -"Target client or tool"New value: +"Target client application or development environment"
  2. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and mostly succeeds: it discloses that the operation is read-only and, importantly, that the supplied API key is embedded directly into the output code sample (or a placeholder is used when omitted). It does not mention auth requirements or rate limits, so a small gap remains.

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?

Three tight sentences, front-loaded with the action and outputs, then the key-embedding rule and the read-only status. No filler or redundancy.

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

Completeness4/5

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

For a 2-parameter generator with no output schema, the description adequately conveys what is returned (Markdown guides and snippets). The one gap is that it lists five client targets but omits 'claude_desktop,' which is a valid enum value, leaving an agent unaware that target is supported.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds a rule the schema omits: apiKey is embedded 'or placeholder if omitted,' clarifying that the parameter is optional in effect. The client parameter is only echoed, not extended beyond the enum.

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?

States a specific verb and resource ('Generate formatted Markdown setup guides and copy-paste configuration snippets') and enumerates the concrete targets (Cursor, Continue, Cline, Chatbox, Python/Node SDKs). The purpose is unmistakably distinct from siblings like list_models or chat_completion, though it never explicitly contrasts itself with them.

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?

The phrase 'for integrating WarungCyber into...' implies the when-to-use context (onboarding/setup), but there is no explicit guidance on when to prefer this over other tools, no prerequisites, and no stated exclusions. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.