mirror of
https://github.com/claude-code-best/claude-code.git
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feat: 添加 skill learning 技能学习闭环系统
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
unraid
229
src/services/skillSearch/__tests__/intentNormalize.test.ts
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229
src/services/skillSearch/__tests__/intentNormalize.test.ts
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@@ -0,0 +1,229 @@
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import { afterEach, beforeEach, describe, expect, mock, test } from 'bun:test'
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// Must mock queryHaiku before importing the module under test so the ESM
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// import binding picks up the stub.
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const haikuCalls: Array<{ systemPrompt: unknown; userPrompt: string }> = []
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let haikuResponder: (userPrompt: string) => Promise<unknown> = async () => ({
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message: { content: [{ type: 'text', text: 'optimize code performance' }] },
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})
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mock.module('../../api/claude.js', () => ({
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queryHaiku: mock(
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async (args: { systemPrompt: unknown; userPrompt: string }) => {
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haikuCalls.push({
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systemPrompt: args.systemPrompt,
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userPrompt: args.userPrompt,
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})
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return haikuResponder(args.userPrompt)
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},
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),
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}))
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import {
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clearIntentNormalizeCache,
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isIntentNormalizeEnabled,
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normalizeQueryIntent,
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} from '../intentNormalize.js'
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const originalEnv = { ...process.env }
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beforeEach(() => {
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process.env = { ...originalEnv }
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haikuCalls.length = 0
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: 'optimize code performance' }] },
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})
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clearIntentNormalizeCache()
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})
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afterEach(() => {
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process.env = { ...originalEnv }
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clearIntentNormalizeCache()
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})
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describe('isIntentNormalizeEnabled', () => {
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test('defaults to disabled when flag is unset', () => {
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delete process.env.SKILL_SEARCH_INTENT_ENABLED
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expect(isIntentNormalizeEnabled()).toBe(false)
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})
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test('enabled when flag is "1"', () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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expect(isIntentNormalizeEnabled()).toBe(true)
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})
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test('disabled for any value other than "1"', () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = 'true'
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expect(isIntentNormalizeEnabled()).toBe(false)
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})
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})
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describe('normalizeQueryIntent — feature flag gating', () => {
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test('returns query unchanged when flag is off', async () => {
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delete process.env.SKILL_SEARCH_INTENT_ENABLED
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const result = await normalizeQueryIntent('帮我优化代码的性能')
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expect(result).toBe('帮我优化代码的性能')
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expect(haikuCalls.length).toBe(0)
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})
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test('returns empty string as-is without calling Haiku', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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const result = await normalizeQueryIntent('')
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expect(result).toBe('')
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expect(haikuCalls.length).toBe(0)
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})
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test('trims whitespace-only input to empty string', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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const result = await normalizeQueryIntent(' \n ')
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expect(result).toBe('')
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expect(haikuCalls.length).toBe(0)
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})
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})
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describe('normalizeQueryIntent — ASCII fast path', () => {
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test('ASCII query bypasses Haiku and returns unchanged', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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const result = await normalizeQueryIntent('optimize code performance')
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expect(result).toBe('optimize code performance')
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expect(haikuCalls.length).toBe(0)
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})
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test('ASCII query with punctuation still bypasses Haiku', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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const result = await normalizeQueryIntent('audit feature flags for stubs')
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expect(result).toBe('audit feature flags for stubs')
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expect(haikuCalls.length).toBe(0)
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})
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})
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describe('normalizeQueryIntent — CJK path calls Haiku', () => {
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test('CJK query concatenates keywords returned by Haiku', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: {
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content: [{ type: 'text', text: 'optimize code performance refactor' }],
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},
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})
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const result = await normalizeQueryIntent('帮我优化代码的性能')
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expect(haikuCalls.length).toBe(1)
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expect(result).toBe('帮我优化代码的性能 optimize code performance refactor')
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})
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test('mixed CJK + ASCII query also calls Haiku', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: 'review code audit' }] },
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})
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const result = await normalizeQueryIntent('帮我做 code review')
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expect(haikuCalls.length).toBe(1)
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expect(result).toBe('帮我做 code review review code audit')
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})
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test('Haiku output gets sanitized: lowercased, punctuation stripped', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: {
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content: [{ type: 'text', text: 'Optimize, Code! Performance?' }],
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},
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})
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const result = await normalizeQueryIntent('优化代码')
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expect(result).toBe('优化代码 optimize code performance')
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})
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})
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describe('normalizeQueryIntent — graceful fallback', () => {
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test('empty LLM response falls back to original query', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: '' }] },
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})
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const result = await normalizeQueryIntent('优化代码')
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expect(result).toBe('优化代码')
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expect(haikuCalls.length).toBe(1)
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})
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test('Haiku throwing an error falls back to original query', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => {
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throw new Error('network down')
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}
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const result = await normalizeQueryIntent('重构代码')
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expect(result).toBe('重构代码')
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expect(haikuCalls.length).toBe(1)
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})
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test('malformed LLM response (no text blocks) falls back', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({ message: { content: 'not-an-array' } })
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const result = await normalizeQueryIntent('优化代码')
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expect(result).toBe('优化代码')
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})
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test('LLM responds with only punctuation -> sanitize empties it -> fallback', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: '!!!???' }] },
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})
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const result = await normalizeQueryIntent('优化代码')
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expect(result).toBe('优化代码')
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})
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})
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describe('normalizeQueryIntent — cache behavior', () => {
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test('repeat calls with same query use cache (only 1 Haiku call)', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: 'optimize code' }] },
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})
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const a = await normalizeQueryIntent('帮我优化代码')
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const b = await normalizeQueryIntent('帮我优化代码')
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const c = await normalizeQueryIntent('帮我优化代码')
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expect(a).toBe(b)
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expect(b).toBe(c)
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expect(haikuCalls.length).toBe(1)
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})
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test('different queries trigger separate Haiku calls', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async (userPrompt: string) => ({
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message: {
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content: [{ type: 'text', text: `kw-for-${userPrompt.slice(0, 2)}` }],
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},
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})
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await normalizeQueryIntent('优化代码')
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await normalizeQueryIntent('重构模块')
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expect(haikuCalls.length).toBe(2)
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})
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test('clearIntentNormalizeCache resets the cache', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: 'kw' }] },
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})
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await normalizeQueryIntent('优化代码')
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clearIntentNormalizeCache()
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await normalizeQueryIntent('优化代码')
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expect(haikuCalls.length).toBe(2)
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})
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})
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describe('normalizeQueryIntent — input capping', () => {
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test('very long CJK input is truncated to 500 chars before sending to Haiku', async () => {
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process.env.SKILL_SEARCH_INTENT_ENABLED = '1'
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const longInput = '优化代码'.repeat(300) // 1200 chars
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haikuResponder = async () => ({
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message: { content: [{ type: 'text', text: 'optimize code' }] },
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})
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await normalizeQueryIntent(longInput)
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expect(haikuCalls[0]?.userPrompt.length).toBeLessThanOrEqual(500)
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})
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})
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221
src/services/skillSearch/__tests__/localSearch.test.ts
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221
src/services/skillSearch/__tests__/localSearch.test.ts
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import { describe, expect, test } from 'bun:test'
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import {
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searchSkills,
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tokenize,
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tokenizeAndStem,
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type SkillIndexEntry,
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} from '../localSearch.js'
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function makeEntry(overrides: Partial<SkillIndexEntry>): SkillIndexEntry {
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const tokens = overrides.tokens ?? []
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const tfVector = overrides.tfVector ?? buildTfVector(tokens)
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const name = overrides.name ?? 'test-skill'
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return {
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name,
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normalizedName:
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overrides.normalizedName ?? name.toLowerCase().replace(/[-_]/g, ' '),
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description: overrides.description ?? '',
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whenToUse: overrides.whenToUse,
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source: overrides.source ?? 'test',
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loadedFrom: overrides.loadedFrom,
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skillRoot: overrides.skillRoot,
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contentLength: overrides.contentLength,
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tokens,
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tfVector,
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}
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}
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function buildTfVector(tokens: string[]): Map<string, number> {
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const freq = new Map<string, number>()
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for (const t of tokens) freq.set(t, (freq.get(t) ?? 0) + 1)
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const max = Math.max(...freq.values(), 1)
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const tf = new Map<string, number>()
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for (const [term, count] of freq) tf.set(term, count / max)
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return tf
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}
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describe('tokenize — CJK bi-gram + ASCII', () => {
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test('优化重构流程 produces five overlapping bi-grams', () => {
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const tokens = tokenize('优化重构流程')
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expect(tokens).toContain('优化')
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expect(tokens).toContain('化重')
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expect(tokens).toContain('重构')
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expect(tokens).toContain('构流')
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expect(tokens).toContain('流程')
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expect(tokens.length).toBe(5)
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})
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test('pure ASCII input retains prior behaviour (regression)', () => {
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const tokens = tokenize('Refactor TypeScript helpers')
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expect(tokens).toContain('refactor')
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expect(tokens).toContain('typescript')
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expect(tokens).toContain('helpers')
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})
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test('mixed Chinese + English is segmented on both sides', () => {
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const tokens = tokenize('优化 refactor 流程')
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expect(tokens).toContain('优化')
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expect(tokens).toContain('流程')
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expect(tokens).toContain('refactor')
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// Adjacent CJK segments are separated by ASCII content, so no cross-segment
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// bi-gram should appear.
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expect(tokens).not.toContain('化流')
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})
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test('isolated single Chinese character produces no bi-gram', () => {
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const tokens = tokenize('优 is lonely')
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expect(tokens.some(t => /[\u4e00-\u9fff]/.test(t))).toBe(false)
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expect(tokens).toContain('lonely')
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})
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test('ASCII stop words still filtered in mixed input', () => {
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const tokens = tokenize('the 优化 is fast')
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expect(tokens).not.toContain('the')
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expect(tokens).not.toContain('is')
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expect(tokens).toContain('优化')
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expect(tokens).toContain('fast')
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})
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})
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describe('tokenizeAndStem — CJK passes through, ASCII stemmed', () => {
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test('CJK bi-grams are not stemmed', () => {
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const tokens = tokenizeAndStem('优化流程')
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expect(tokens).toContain('优化')
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expect(tokens).toContain('化流')
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expect(tokens).toContain('流程')
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})
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test('ASCII words are stemmed while CJK survives', () => {
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const tokens = tokenizeAndStem('refactoring 重构 helpers')
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expect(tokens).toContain('refactor')
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expect(tokens).toContain('重构')
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expect(tokens).toContain('helper')
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})
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})
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describe('searchSkills — CJK query against skill index', () => {
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test('Chinese query against Chinese-metadata skill produces positive score', () => {
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const chineseSkillTokens = tokenizeAndStem(
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'refactor-cleaner 清理 重构 流程 的工具',
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)
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const unrelatedTokens = tokenizeAndStem(
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'database-migration tool for schema upgrades',
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)
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const index: SkillIndexEntry[] = [
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makeEntry({
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name: 'refactor-cleaner',
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description: '清理和重构流程辅助',
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tokens: chineseSkillTokens,
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}),
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makeEntry({
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name: 'database-migration',
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description: 'schema upgrade',
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tokens: unrelatedTokens,
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}),
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]
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const results = searchSkills('优化重构流程', index, 5)
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expect(results.length).toBeGreaterThan(0)
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expect(results[0]?.name).toBe('refactor-cleaner')
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expect(results[0]?.score).toBeGreaterThan(0)
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})
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test('pure English query still ranks English skill first (regression)', () => {
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const refactorTokens = tokenizeAndStem(
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'refactor clean typescript code helper',
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)
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const unrelatedTokens = tokenizeAndStem(
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'security review audit vulnerabilities',
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)
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const index: SkillIndexEntry[] = [
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makeEntry({
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name: 'refactor-helper',
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description: 'refactor typescript',
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tokens: refactorTokens,
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}),
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makeEntry({
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name: 'security-review',
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description: 'security audit',
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tokens: unrelatedTokens,
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}),
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]
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const results = searchSkills('refactor typescript', index, 5)
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expect(results[0]?.name).toBe('refactor-helper')
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})
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test('CJK query with only 1 matching bi-gram is filtered out (Proposal D)', () => {
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const promptOptTokens = tokenizeAndStem(
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'prompt-optimizer optimize prompts for better performance 当前最佳实践',
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)
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const otherTokens = tokenizeAndStem(
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'database-migration tool for schema upgrades',
|
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)
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const index: SkillIndexEntry[] = [
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makeEntry({
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name: 'prompt-optimizer',
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description: 'optimize prompts',
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tokens: promptOptTokens,
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}),
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makeEntry({
|
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name: 'database-migration',
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description: 'schema upgrade',
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tokens: otherTokens,
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}),
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]
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const results = searchSkills('研究当前代码', index, 5)
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expect(results.length).toBe(0)
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})
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test('CJK query with 2+ matching bi-grams passes the gate', () => {
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const refactorTokens = tokenizeAndStem(
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'refactor-cleaner 代码重构 清理冗余代码',
|
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)
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const unrelatedTokens = tokenizeAndStem(
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'database-migration tool for schema upgrades',
|
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)
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const index: SkillIndexEntry[] = [
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makeEntry({
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name: 'refactor-cleaner',
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description: '代码重构清理',
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tokens: refactorTokens,
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}),
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||||
makeEntry({
|
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name: 'database-migration',
|
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description: 'schema upgrade',
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tokens: unrelatedTokens,
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}),
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]
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||||
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const results = searchSkills('重构代码', index, 5)
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expect(results.length).toBeGreaterThan(0)
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expect(results[0]?.name).toBe('refactor-cleaner')
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})
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test('exact skill name in query boosts score (Proposal C)', () => {
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const codeReviewTokens = tokenizeAndStem('code-review review code quality')
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const securityTokens = tokenizeAndStem('security-review review security')
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const index: SkillIndexEntry[] = [
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makeEntry({
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name: 'code-review',
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description: 'review code quality',
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tokens: codeReviewTokens,
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||||
}),
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||||
makeEntry({
|
||||
name: 'security-review',
|
||||
description: 'review security',
|
||||
tokens: securityTokens,
|
||||
}),
|
||||
]
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||||
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const results = searchSkills('code review', index, 5)
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expect(results[0]?.name).toBe('code-review')
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expect(results[0]!.score).toBeGreaterThanOrEqual(0.75)
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||||
})
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||||
})
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||||
123
src/services/skillSearch/__tests__/prefetch.extractQuery.test.ts
Normal file
123
src/services/skillSearch/__tests__/prefetch.extractQuery.test.ts
Normal file
@@ -0,0 +1,123 @@
|
||||
import { describe, expect, test } from 'bun:test'
|
||||
import { extractQueryFromMessages } from '../prefetch.js'
|
||||
import type { Message } from '../../../types/message.js'
|
||||
|
||||
function userText(text: string): Message {
|
||||
return { type: 'user', content: text } as unknown as Message
|
||||
}
|
||||
|
||||
function userTextBlocks(text: string): Message {
|
||||
return {
|
||||
type: 'user',
|
||||
content: [{ type: 'text', text }],
|
||||
} as unknown as Message
|
||||
}
|
||||
|
||||
function userToolResult(id: string): Message {
|
||||
return {
|
||||
type: 'user',
|
||||
content: [{ type: 'tool_result', tool_use_id: id, content: 'output' }],
|
||||
} as unknown as Message
|
||||
}
|
||||
|
||||
function assistantText(text: string): Message {
|
||||
return { type: 'assistant', content: text } as unknown as Message
|
||||
}
|
||||
|
||||
describe('extractQueryFromMessages — inter-turn穿透逻辑', () => {
|
||||
test('null input + messages末尾是tool_result → 穿透到真实user文本', () => {
|
||||
const messages: Message[] = [
|
||||
userText('研究当前代码'),
|
||||
assistantText('调用工具'),
|
||||
userToolResult('tool_01'),
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('研究当前代码')
|
||||
})
|
||||
|
||||
test('null input + messages末尾是text block形式的user → 正确提取', () => {
|
||||
const messages: Message[] = [
|
||||
userTextBlocks('refactor the auth module'),
|
||||
assistantText('thinking...'),
|
||||
userToolResult('tool_02'),
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('refactor the auth module')
|
||||
})
|
||||
|
||||
test('null input + 连续多轮tool_result → 继续向前找到最早的user文本', () => {
|
||||
const messages: Message[] = [
|
||||
userText('研究当前代码'),
|
||||
assistantText('第一次调用'),
|
||||
userToolResult('tool_a'),
|
||||
assistantText('第二次调用'),
|
||||
userToolResult('tool_b'),
|
||||
assistantText('第三次调用'),
|
||||
userToolResult('tool_c'),
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('研究当前代码')
|
||||
})
|
||||
|
||||
test('null input + 空messages → 空串', () => {
|
||||
const query = extractQueryFromMessages(null, [])
|
||||
expect(query).toBe('')
|
||||
})
|
||||
|
||||
test('null input + 全是tool_result (无真实文本) → 空串', () => {
|
||||
const messages: Message[] = [
|
||||
userToolResult('tool_a'),
|
||||
userToolResult('tool_b'),
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('')
|
||||
})
|
||||
|
||||
test('string input + null messages → 只返回input', () => {
|
||||
const query = extractQueryFromMessages('hello world', [])
|
||||
expect(query).toBe('hello world')
|
||||
})
|
||||
|
||||
test('string input + 有user文本 → 两者拼接', () => {
|
||||
const messages: Message[] = [userText('previous query')]
|
||||
const query = extractQueryFromMessages('new query', messages)
|
||||
expect(query).toContain('new query')
|
||||
expect(query).toContain('previous query')
|
||||
})
|
||||
|
||||
test('超长user文本被截断到500字', () => {
|
||||
const longText = 'a'.repeat(1000)
|
||||
const messages: Message[] = [userText(longText)]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query.length).toBe(500)
|
||||
})
|
||||
|
||||
test('tool_result里含text字段 (但type=tool_result) → 必须跳过，不能误用', () => {
|
||||
const messages: Message[] = [
|
||||
userText('real query'),
|
||||
{
|
||||
type: 'user',
|
||||
content: [
|
||||
{
|
||||
type: 'tool_result',
|
||||
text: 'this is tool output masquerading as text',
|
||||
},
|
||||
],
|
||||
} as unknown as Message,
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('real query')
|
||||
})
|
||||
|
||||
test('user content数组里text为空串 → 跳过空text继续找', () => {
|
||||
const messages: Message[] = [
|
||||
userText('real query'),
|
||||
{
|
||||
type: 'user',
|
||||
content: [{ type: 'text', text: ' ' }],
|
||||
} as unknown as Message,
|
||||
]
|
||||
const query = extractQueryFromMessages(null, messages)
|
||||
expect(query).toBe('real query')
|
||||
})
|
||||
})
|
||||
101
src/services/skillSearch/__tests__/prefetch.test.ts
Normal file
101
src/services/skillSearch/__tests__/prefetch.test.ts
Normal file
@@ -0,0 +1,101 @@
|
||||
import { afterEach, beforeEach, describe, expect, test } from 'bun:test'
|
||||
import {
|
||||
existsSync,
|
||||
mkdirSync,
|
||||
mkdtempSync,
|
||||
rmSync,
|
||||
writeFileSync,
|
||||
} from 'node:fs'
|
||||
import { tmpdir } from 'node:os'
|
||||
import { join } from 'node:path'
|
||||
import { clearCommandsCache } from '../../../commands.js'
|
||||
import { getTurnZeroSkillDiscovery } from '../prefetch.js'
|
||||
import { clearSkillIndexCache } from '../localSearch.js'
|
||||
|
||||
let root: string
|
||||
let previousCwd: string
|
||||
const originalEnv = { ...process.env }
|
||||
|
||||
beforeEach(() => {
|
||||
root = mkdtempSync(join(tmpdir(), 'skill-search-prefetch-'))
|
||||
previousCwd = process.cwd()
|
||||
process.chdir(root)
|
||||
process.env = { ...originalEnv }
|
||||
process.env.CLAUDE_CONFIG_DIR = join(root, 'config')
|
||||
process.env.CLAUDE_SKILL_LEARNING_HOME = join(root, 'learning')
|
||||
process.env.SKILL_SEARCH_ENABLED = '1'
|
||||
process.env.SKILL_LEARNING_ENABLED = '1'
|
||||
process.env.NODE_ENV = 'test'
|
||||
process.env.ANTHROPIC_API_KEY = 'test-key'
|
||||
clearCommandsCache()
|
||||
clearSkillIndexCache()
|
||||
})
|
||||
|
||||
afterEach(() => {
|
||||
process.chdir(previousCwd)
|
||||
process.env = { ...originalEnv }
|
||||
clearCommandsCache()
|
||||
clearSkillIndexCache()
|
||||
try {
|
||||
rmSync(root, {
|
||||
recursive: true,
|
||||
force: true,
|
||||
maxRetries: 10,
|
||||
retryDelay: 100,
|
||||
})
|
||||
} catch {
|
||||
// Windows can keep transient handles after dynamic command loading.
|
||||
}
|
||||
})
|
||||
|
||||
describe('skill search prefetch', () => {
|
||||
test('auto-loads high-confidence project skill content', async () => {
|
||||
const skillDir = join(root, '.claude', 'skills', 'feature-audit')
|
||||
mkdirSync(skillDir, { recursive: true })
|
||||
writeFileSync(
|
||||
join(skillDir, 'SKILL.md'),
|
||||
[
|
||||
'---',
|
||||
'name: feature-audit',
|
||||
'description: Audit feature flags and classify minimal implementations',
|
||||
'---',
|
||||
'',
|
||||
'# Feature Audit',
|
||||
'',
|
||||
'Use the feature flag audit workflow and classify flags as stub, shell, MVP, or thin-toggle.',
|
||||
].join('\n'),
|
||||
)
|
||||
|
||||
const attachment = await getTurnZeroSkillDiscovery(
|
||||
'audit feature flags for minimal implementation stubs',
|
||||
[],
|
||||
{ agentId: undefined } as any,
|
||||
)
|
||||
|
||||
expect(attachment?.type).toBe('skill_discovery')
|
||||
if (attachment?.type !== 'skill_discovery') {
|
||||
throw new Error('expected skill_discovery attachment')
|
||||
}
|
||||
expect(attachment.skills[0]?.name).toBe('feature-audit')
|
||||
expect(attachment.skills[0]?.autoLoaded).toBe(true)
|
||||
expect(attachment.skills[0]?.content).toContain(
|
||||
'feature flag audit workflow',
|
||||
)
|
||||
})
|
||||
|
||||
test('records a pending skill gap on the first unmatched prompt (no draft file yet)', async () => {
|
||||
const attachment = await getTurnZeroSkillDiscovery(
|
||||
'frobnicate zephyr ledger workflow',
|
||||
[],
|
||||
{ agentId: undefined } as any,
|
||||
)
|
||||
|
||||
expect(attachment?.type).toBe('skill_discovery')
|
||||
if (attachment?.type !== 'skill_discovery') {
|
||||
throw new Error('expected skill_discovery attachment')
|
||||
}
|
||||
expect(attachment.skills).toEqual([])
|
||||
expect(attachment.gap?.status).toBe('pending')
|
||||
expect(attachment.gap?.draftPath).toBeUndefined()
|
||||
})
|
||||
})
|
||||
Reference in New Issue
Block a user