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Build apps, websites, and AI agents in English. Zero-interaction setup for AI agents (Claude Code, Cursor, Windsurf). Download to your computer, run in the cloud, deploy to the edge. Open source and free forever.

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--- title: Tests dimension: things category: cascade tags: agent, ai, knowledge related_dimensions: knowledge, people scope: global created: 2025-11-03 updated: 2025-11-03 version: 1.0.0 ai_context: | This document is part of the things dimension in the cascade category. Location: one/things/cascade/docs/examples/1-4-knowledge-management/tests.md Purpose: Documents tests for feature 1-4: knowledge management system Related dimensions: knowledge, people For AI agents: Read this to understand tests. --- # Tests for Feature 1-4: Knowledge Management System **Feature:** 1-4-knowledge-management **Status:** Tests Defined → Design Phase **Quality Agent:** agent-quality.md --- ## User Flows ### Flow 1: Capture Lesson Learned **User goal:** Specialist adds lesson after fixing problem **Time budget:** < 2 minutes to write lesson **Steps:** 1. Specialist fixes problem 2. Specialist opens `lessons-learned.md` 3. Specialist writes lesson with template 4. Specialist includes problem, solution, pattern 5. Lesson saved 6. Lesson searchable immediately **Acceptance Criteria:** - [ ] Lesson template clear and easy to follow - [ ] Required fields enforced (problem, solution, pattern) - [ ] Lesson written in < 2 minutes - [ ] Lesson added to correct category - [ ] Lesson includes example code - [ ] Lesson immediately searchable --- ### Flow 2: Search Knowledge Base **User goal:** Problem solver finds similar issues **Time budget:** < 5 seconds **Steps:** 1. Problem solver analyzes test failure 2. Problem solver searches lessons learned 3. System returns relevant lessons 4. Problem solver reviews results 5. Problem solver references similar issue or creates new **Acceptance Criteria:** - [ ] Search by keywords: < 5 seconds - [ ] Search by category: < 2 seconds - [ ] Results ranked by relevance - [ ] Returns 0-10 most relevant lessons - [ ] Highlights matching text - [ ] Search works even with typos --- ### Flow 3: Load Pattern Template **User goal:** Specialist applies pattern to implementation **Time budget:** < 3 seconds **Steps:** 1. Specialist needs to implement feature 2. Specialist loads relevant pattern 3. Pattern template displayed 4. Specialist copies and adapts template 5. Implementation follows pattern **Acceptance Criteria:** - [ ] Pattern loaded: < 1 second - [ ] Template includes placeholders - [ ] Variables documented - [ ] Example included - [ ] Usage instructions clear - [ ] Common mistakes documented --- ### Flow 4: Promote Lesson to Pattern **User goal:** System recognizes repeated lesson becomes pattern **Time budget:** < 10 minutes to create pattern **Steps:** 1. Same lesson appears 3+ times 2. System or human identifies repetition 3. Extract common structure 4. Create pattern template with variables 5. Document in patterns/ directory 6. Future lessons reference pattern **Acceptance Criteria:** - [ ] Repeated lessons detected (3+ occurrences) - [ ] Pattern creation guided by template - [ ] Pattern includes all required sections - [ ] Pattern documented clearly - [ ] Pattern referenced from lessons - [ ] Future work uses pattern --- ### Flow 5: Knowledge Accumulation Over Time **User goal:** System gets smarter with each problem solved **Time budget:** Ongoing **Steps:** 1. Week 1: 0 lessons, 8 basic patterns 2. Month 1: 20+ lessons, 8 patterns 3. Month 3: 60+ lessons, 15 patterns (7 promoted) 4. Quarter 1: 150+ lessons, 25+ patterns 5. Features built faster (reference existing knowledge) **Acceptance Criteria:** - [ ] Lessons accumulate continuously - [ ] Patterns promoted from lessons - [ ] Knowledge referenced in new work - [ ] Repeat problems decrease over time - [ ] Feature velocity increases - [ ] Quality improves continuously --- ## Technical Tests ### Unit Tests **Lesson Capture:** - [ ] `addLesson(lesson)` validates structure - [ ] `addLesson()` requires problem, solution, pattern - [ ] `addLesson()` adds to correct category - [ ] `addLesson()` generates lesson ID - [ ] `addLesson()` logs event **Knowledge Search:** - [ ] `search(query)` returns ranked results - [ ] `search(query, category)` filters by category - [ ] `getLessons(category, limit)` returns recent lessons - [ ] `getPattern(category, name)` returns pattern - [ ] `getRelated(lessonId)` finds related lessons **Pattern Management:** - [ ] `createPattern(lesson)` extracts template - [ ] `createPattern()` identifies variables - [ ] `createPattern()` documents usage - [ ] `loadPattern(name)` returns template --- ### Integration Tests **Lesson to Pattern Promotion:** - [ ] Detect 3 similar lessons - [ ] Extract common structure - [ ] Create pattern template - [ ] Update lessons to reference pattern - [ ] Future work uses pattern **Knowledge in Workflow:** - [ ] Problem solver searches lessons - [ ] Problem solver references similar issues - [ ] Specialist loads patterns - [ ] Specialist applies patterns - [ ] Specialist captures new lessons **Knowledge Accumulation:** - [ ] Week 1: 5 lessons added - [ ] Month 1: 20 lessons total - [ ] Month 3: Pattern promoted - [ ] Quarter 1: 25+ patterns --- ### E2E Tests **Complete Knowledge Cycle:** - [ ] Problem occurs (test fails) - [ ] Problem solver analyzes - [ ] Problem solver searches lessons (finds 0) - [ ] Specialist fixes problem - [ ] Specialist captures lesson - [ ] Lesson searchable - [ ] Future problem: lesson found - [ ] 3rd occurrence: pattern promoted **Knowledge Impact:** - [ ] Month 1: 20% problems repeat - [ ] Month 3: 10% problems repeat (lessons help) - [ ] Quarter 1: 5% problems repeat (patterns prevent) - [ ] Feature velocity increases 2x (less figuring out) --- ## Definition of Done - [ ] Lessons learned structure defined - [ ] Pattern library organized - [ ] 8 basic patterns created - [ ] Knowledge query system works - [ ] Lesson capture workflow documented - [ ] Pattern discovery process defined - [ ] All tests pass --- **Next:** Design phase - Knowledge base structure and search architecture