Audit Console Phase 1: tool_call_trace emission from mcplocal router,
session_bind/rbac_decision event kinds, GET /audit/sessions endpoint,
full Ink TUI with session sidebar, event timeline, and detail view
(mcpctl console --audit).
System prompts: move 6 hardcoded LLM prompts to mcpctl-system project
with extensible ResourceRuleRegistry validation framework, template
variable enforcement ({{maxTokens}}, {{pageCount}}), and delete-resets-
to-default behavior. All consumers fetch via SystemPromptFetcher with
hardcoded fallbacks.
CLI: -p shorthand for --project across get/create/delete/config commands,
console auto-scroll improvements, shell completions regenerated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
161 lines
5.2 KiB
TypeScript
161 lines
5.2 KiB
TypeScript
import { describe, it, expect, vi } from 'vitest';
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import type { StageContext, LLMProvider, CacheProvider, StageLogger, SystemPromptFetcher } from '../src/proxymodel/types.js';
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import paginate from '../src/proxymodel/stages/paginate.js';
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import summarizeTree from '../src/proxymodel/stages/summarize-tree.js';
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function mockCtx(
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original: string,
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config: Record<string, unknown> = {},
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opts: { llmAvailable?: boolean; getSystemPrompt?: SystemPromptFetcher } = {},
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): StageContext {
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const mockLlm: LLMProvider = {
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async complete(prompt) {
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// For paginate: return JSON array of titles
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if (prompt.includes('short descriptive titles') || prompt.includes('JSON array')) {
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return '["Title A", "Title B"]';
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}
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// For summarize: return a summary
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return `Summary of: ${prompt.slice(0, 40)}...`;
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},
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available: () => opts.llmAvailable ?? false,
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};
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const cache = new Map<string, string>();
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const mockCache: CacheProvider = {
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async getOrCompute(key, compute) {
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if (cache.has(key)) return cache.get(key)!;
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const val = await compute();
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cache.set(key, val);
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return val;
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},
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hash(content) { return content.slice(0, 8); },
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async get(key) { return cache.get(key) ?? null; },
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async set(key, value) { cache.set(key, value); },
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};
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const mockLog: StageLogger = {
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debug: vi.fn(),
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info: vi.fn(),
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warn: vi.fn(),
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error: vi.fn(),
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};
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return {
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contentType: 'toolResult',
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sourceName: 'test/tool',
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projectName: 'test',
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sessionId: 'sess-1',
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originalContent: original,
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llm: mockLlm,
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cache: mockCache,
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log: mockLog,
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getSystemPrompt: opts.getSystemPrompt ?? (async (_name, fallback) => fallback),
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config,
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};
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}
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describe('System prompt fetching in stages', () => {
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describe('paginate stage', () => {
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it('uses getSystemPrompt to fetch paginate-titles prompt', async () => {
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const fetchSpy = vi.fn(async (_name: string, fallback: string) => fallback);
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const content = 'A'.repeat(9000); // Larger than default pageSize (8000)
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const ctx = mockCtx(content, {}, { llmAvailable: true, getSystemPrompt: fetchSpy });
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await paginate(content, ctx);
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expect(fetchSpy).toHaveBeenCalledWith(
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'llm-paginate-titles',
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expect.stringContaining('{{pageCount}}'),
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);
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});
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it('falls back to hardcoded default when fetcher returns fallback', async () => {
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const content = 'B'.repeat(9000);
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const ctx = mockCtx(content, {}, { llmAvailable: true });
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const result = await paginate(content, ctx);
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// Should still produce paginated output (uses default prompt)
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expect(result.content).toContain('pages');
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});
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it('interpolates {{pageCount}} in the fetched template', async () => {
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let capturedPrompt = '';
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const customFetcher: SystemPromptFetcher = async (name, fallback) => {
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if (name === 'llm-paginate-titles') {
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return 'Custom: generate {{pageCount}} titles please';
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}
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return fallback;
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};
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const mockLlm: LLMProvider = {
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async complete(prompt) {
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capturedPrompt = prompt;
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return '["A", "B"]';
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},
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available: () => true,
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};
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const content = 'C'.repeat(9000);
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const ctx = mockCtx(content, {}, { llmAvailable: true, getSystemPrompt: customFetcher });
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// Override llm to capture the prompt
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(ctx as { llm: LLMProvider }).llm = mockLlm;
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await paginate(content, ctx);
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expect(capturedPrompt).toContain('Custom: generate 2 titles please');
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expect(capturedPrompt).not.toContain('{{pageCount}}');
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});
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});
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describe('summarize-tree stage', () => {
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it('uses getSystemPrompt to fetch llm-summarize prompt', async () => {
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const fetchSpy = vi.fn(async (_name: string, fallback: string) => fallback);
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// Need prose content > 2000 chars with headers to trigger LLM summary
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const sections = [
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'# Section 1\n' + 'Word '.repeat(500),
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'# Section 2\n' + 'Text '.repeat(500),
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].join('\n\n');
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const ctx = mockCtx(sections, {}, { llmAvailable: true, getSystemPrompt: fetchSpy });
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await summarizeTree(sections, ctx);
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expect(fetchSpy).toHaveBeenCalledWith(
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'llm-summarize',
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expect.stringContaining('{{maxTokens}}'),
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);
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});
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it('interpolates {{maxTokens}} in the fetched template', async () => {
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let capturedPrompt = '';
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const customFetcher: SystemPromptFetcher = async (name, fallback) => {
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if (name === 'llm-summarize') {
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return 'Custom summary in {{maxTokens}} tokens max';
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}
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return fallback;
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};
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const mockLlm: LLMProvider = {
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async complete(prompt) {
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capturedPrompt = prompt;
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return 'A brief summary';
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},
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available: () => true,
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};
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const sections = [
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'# Part A\n' + 'Content '.repeat(500),
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'# Part B\n' + 'More '.repeat(500),
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].join('\n\n');
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const ctx = mockCtx(sections, {}, { llmAvailable: true, getSystemPrompt: customFetcher });
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(ctx as { llm: LLMProvider }).llm = mockLlm;
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await summarizeTree(sections, ctx);
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expect(capturedPrompt).toContain('Custom summary in 200 tokens max');
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expect(capturedPrompt).not.toContain('{{maxTokens}}');
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});
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});
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});
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