implement-python-tool

A command that implements one Python tool from a GitHub issue in the MCP DevTools Server project. MCP is a way for applications to expose tools that an AI assistant can call, and the command follows the project's existing Go-tool patterns with caching.

In plain words
What is it for?
Use it with an issue number to create or update Python tool support, add tests, follow existing project conventions, and verify linting, tests, and the build.
Why use it?
It gives the implementation agent a defined research, coding, testing, and validation process instead of requiring the same setup work each time.

Command for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/rshade/mcp-devtools-server/implement-python-tool
Clone the repo
git clone --depth 1 https://github.com/rshade/mcp-devtools-server

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,313 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01313
Opus 5 $0.00000 $0.00656
Sonnet 5 $0.00000 $0.00263
Haiku 4.5 $0.00000 $0.00131

Measured yesterday against content hash 3bf6a52cc08f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implement-python-tool scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/commands/implement-python-tool.md · 187 lines

How it starts

The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implement a Python tool using a specialized Haiku-powered agent.

Usage: /implement-python-tool [issue-number]

This command launches a cost-efficient Haiku agent that implements a single Python tool from the Epic #131 following established patterns with cache optimization.

Example:

/implement-python-tool 132

Implements python_project_info from issue #132.


Launch the Python implementation agent with Haiku model for issue #{{ISSUE_NUMBER}}.

Use the Task tool with:

  • subagent_type: general-purpose
  • model: haiku
  • prompt: Detailed implementation instructions below

Task for Agent:

You are implementing Python tool support for MCP DevTools Server. Your mission: Implement the tool specified in GitHub issue #{{ISSUE_NUMBER}} following the exact Go tools pattern with cache optimization built in.

Phase 1: Research (Read these files)

  1. Read issue: gh issue view {{ISSUE_NUMBER}} --repo rshade/mcp-devtools-server
  2. Read Go tools reference: src/tools/go-tools.ts (focus on structure)
  3. Read cache patterns: src/utils/cache-manager.ts and CACHING.md
  4. Read test patterns: src/__tests__/tools/go-tools.test.ts

Phase 2: Implementation

Create src/tools/python-tools.ts (or add to existing) following this structure:

import { z } from 'zod';
import { ShellExecutor } from '../utils/shell-executor.js';
import { CacheManager } from '../utils/cache-manager.js';
import * as crypto from 'crypto';

// 1. Define Zod schema from issue
const PythonXxxSchema = z.object({
  directory: z.string().optional(),
  // ... parameters from issue
});

type PythonXxxArgs = z.infer<typeof PythonXxxSchema>;

interface PythonToolResult {
  success: boolean;
  data?: any;
  error?: string;
}

export class PythonTools {
  constructor(private shellExecutor: ShellExecutor) {}
  
  // 2. Main tool method WITH CACHING
  async pythonXxx(args: PythonXxxArgs): Promise<PythonToolResult> {
    const validated = PythonXxxSchema.parse(args);
    const directory = validated.directory || process.cwd();
    
    // CACHE CHECK (required, not optional!)
    const cacheKey = this.generateXxxCacheKey(directory, validated);
    const cached = await CacheManager.getInstance().get('python_tools', cacheKey);
    if (cached) return cached as PythonToolResult;
    
    // Build command incrementally
    const cmd = ['tool-name'];
    // ... add args
    
    // Execute
    const result = await this.shellExecutor.executeCommand(
      cmd.join(' '),
      directory,
      { timeout: 60000 }
    );
    
    // Parse
    const parsed = this.parseXxxOutput(result);
    
    // CACHE RESULT (use TTL from issue)
    if (parsed.success) {
      await CacheManager.getInstance().set('python_tools', cacheKey, parsed, TTL);
    }
    
    return parsed;
  }
  
  // 3. Cache key generator
  private generateXxxCacheKey(dir: string, args: PythonXxxArgs): string {
    const params = { /* all parameters */ };
    const hash = crypto.createHash('sha256')
      .update(JSON.stringify(params))
      .digest('hex')
      .substring(0, 16);
    return `python:xxx:${dir}:${hash}`;
  }
  
  // 4. Output parser
  private parseXxxOutput(result: any): PythonToolResult {
    // Parse stdout/stderr from issue examples
    return { success: result.exitCode === 0, data: {} };
  }
  
  // 5. Static validator
  static validatePythonXxx(args: unknown) {
    return PythonXxxSchema.safeParse(args);
  }
}

Phase 3: Testing

Create src/__tests__/tools/python-tools.test.ts:

import { describe, it, expect, beforeEach } from '@jest/globals';
import { PythonTools } from '../../tools/python-tools.js';
import { CacheManager } from '../../utils/cache-manager.js';

describe('PythonTools - pythonXxx', () => {
  let pythonTools: PythonTools;
  let mockShellExecutor: any;
  
  beforeEach(() => {
    CacheManager.resetInstance(); // CRITICAL!
    mockShellExecutor = createMockShellExecutor();
    pythonTools = new PythonTools(mockShellExecutor);
  });
  
  // Test all requirements from issue
  it('executes successfully', async () => { /* ... */ });
  it('caches results', async () => { /* verify callCount === 1 */ });
  it('handles errors', async () => { /* ... */ });
  // ... more tests from issue
});

Read the full file on GitHub · 187 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 187 lines · 0 tokens per session scan A 3bf6a52cc08f

Subscribe to this mod's changes

implement-python-tool is a command published in the GitHub repository rshade/mcp-devtools-server (5 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,313 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.