claude-code-mcp (KunihiroS) — Prompts
All prompts are hardcoded TypeScript string templates in claude-code-server/src/index.ts. They are constructed at request time and piped to claude --print via stdin. There are no separate prompt files.
Prompt 1 — explain_code
const prompt = `You are super professional engineer. Please kindly provide a detailed explanation of the following Base64 encoded code:\n\n${encodedCode}\n\nAdditional context (if provided):\n${context || 'No additional context provided.'}`;
Prompting technique: Role assignment ("You are super professional engineer") + task instruction + Base64-encoded payload embedded inline. The "kindly" qualifier is unusual and likely intended to soften the Claude response style. Persona framing is minimal and informal.
Prompt 2 — review_code
const prompt = `You are super professional engineer. Please review the following Base64 encoded code. Consider code readability, efficiency, potential bugs, and security vulnerabilities.\n\nCode:\n${encodedCode}\n\nFocus areas (if provided):\n${focus_areas || 'No specific focus areas provided.'}`;
Prompting technique: Same role assignment. Explicit enumeration of review dimensions (readability, efficiency, bugs, security) functions as a lightweight checklist injection. Optional focus_areas parameter allows caller-side specialization.
Prompt 3 — fix_code
const prompt = `You are super professional engineer. Please fix the following Base64 encoded code, addressing the issue described below:\n\nCode:\n${encodedCode}\n\nIssue description:\n${issue_description ?? 'No specific issue described.'}`;
Prompting technique: Task-constraint framing ("addressing the issue described below") with inline issue specification.
Prompt 4 — edit_code
const prompt = `You are super professional engineer. Please edit the following Base64 encoded code according to the instructions provided:\n\nCode:\n${encodedCode}\n\nInstructions:\n${instructions ?? 'No specific instructions provided.'}`;
Prompt 5 — test_code
const prompt = `You are super professional engineer. Please generate tests for the following Base64 encoded code.\n\nCode:\n${encodedCode}\n\nTest framework (if specified):\n${framework || 'No specific framework provided. Please use a suitable default framework.'}`;
Prompting technique: Conditional instruction — "if not specified, choose a default" is delegated back to the model.
Prompt 6 — simulate_command
const prompt = `You are super professional engineer. Simulate the execution of the following command:\n\nCommand: ${command}\n\nInput: ${input || 'No input provided.'}\n\nDescribe the expected behavior and output, without actually executing the command.`;
Prompting technique: Explicit safety constraint ("without actually executing the command") — the command string is passed as data, not executed by the prompt.
Prompt 7 — your_own_query
const prompt = `Query: ${query} ${context || ''}`;
Prompting technique: Minimal pass-through — no role injection, no framing. The caller supplies the full semantic content. This is the only tool that doesn't use the "super professional engineer" persona.
Key Observation
All tools except your_own_query and simulate_command pass the code payload as a Base64-encoded string embedded inside the prompt text. This is the framework's primary technical contribution: encoding as a transport mechanism rather than using file-based or multipart input.