Refactor implementation approach structure across task generation files

- Updated implementation_approach in task-generate-tdd.md to use an array format with detailed steps for minimal code implementation and iterative testing.
- Enhanced task-generate.md to support CLI execution mode with Codex, including examples for task execution and session management.
- Modified test-task-generate.md to incorporate CLI execution mode, allowing Codex to autonomously generate tests and execute iterative test-fix cycles.
- Revised task-core.md and workflow-architecture.md to adopt a step-based implementation approach, improving clarity and dependency management in task execution.
- Improved documentation in workflow-architecture.md to clarify flow control structure and variable referencing.
This commit is contained in:
catlog22
2025-10-12 14:09:47 +08:00
parent c5aac313ff
commit 58153ecb83
15 changed files with 1479 additions and 920 deletions

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@@ -41,6 +41,30 @@ You will execute tests, analyze failures, and fix code to ensure all tests pass.
## Execution Process
### Flow Control Execution
When task JSON contains `flow_control` field, execute preparation and implementation steps systematically.
**Pre-Analysis Steps** (`flow_control.pre_analysis`):
1. **Sequential Processing**: Execute steps in order, accumulating context
2. **Variable Substitution**: Use `[variable_name]` to reference previous outputs
3. **Error Handling**: Follow step-specific strategies (`skip_optional`, `fail`, `retry_once`)
**Implementation Approach** (`flow_control.implementation_approach`):
When task JSON contains implementation_approach array:
1. **Sequential Execution**: Process steps in order, respecting `depends_on` dependencies
2. **Dependency Resolution**: Wait for all steps listed in `depends_on` before starting
3. **Variable References**: Use `[variable_name]` to reference outputs from previous steps
4. **Step Structure**:
- `step`: Step number (1, 2, 3...)
- `title`: Step title
- `description`: Detailed description with variable references
- `modification_points`: Test and code modification targets
- `logic_flow`: Test-fix iteration sequence
- `command`: Optional CLI command (only when explicitly specified)
- `depends_on`: Array of step numbers that must complete first
- `output`: Variable name for this step's output
### 1. Context Assessment & Test Discovery
- Analyze task context to identify test files and source code paths
- Load test framework configuration (Jest, Pytest, Mocha, etc.)
@@ -61,16 +85,34 @@ fi
- Parse test results to identify failures
### 3. Failure Diagnosis & Fixing Loop
**Execution Modes**:
**A. Manual Mode (Default, meta.use_codex=false)**:
```
WHILE tests are failing:
1. Analyze failure output
2. Identify root cause in source code
3. Modify source code to fix issue
4. Re-run affected tests
WHILE tests are failing AND iterations < max_iterations:
1. Use Gemini to diagnose failure (bug-fix template)
2. Present fix recommendations to user
3. User applies fixes manually
4. Re-run test suite
5. Verify fix doesn't break other tests
END WHILE
```
**B. Codex Mode (meta.use_codex=true)**:
```
WHILE tests are failing AND iterations < max_iterations:
1. Use Gemini to diagnose failure (bug-fix template)
2. Use Codex to apply fixes automatically with resume mechanism
3. Re-run test suite
4. Verify fix doesn't break other tests
END WHILE
```
**Codex Resume in Test-Fix Cycle** (when `meta.use_codex=true`):
- First iteration: Start new Codex session with full context
- Subsequent iterations: Use `resume --last` to maintain fix history and apply consistent strategies
### 4. Code Quality Certification
- All tests pass → Code is APPROVED ✅
- Generate summary documenting: