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- Create task-schema.json (JSON Schema draft-07) with 10 field blocks fusing Unified JSONL, 6-field Task JSON, and Solution Schema advantages - Migrate unified-execute-with-file from JSONL to .task/*.json directory scanning - Migrate 3 producers (lite-plan, plan-converter, collaborative-plan) to .task/*.json multi-file output - Add review-cycle Phase 7.5 export-to-tasks (FIX-*.json) and issue-resolve --export-tasks option - Add schema compatibility annotations to action-planning-agent, workflow-plan, and tdd-plan - Add spec-generator skill phases and templates - Add memory v2 pipeline (consolidation, extraction, job scheduler, embedder) - Add secret-redactor utility and core-memory enhancements - Add codex-lens accuracy benchmarks and staged env config overrides
7.1 KiB
7.1 KiB
Phase 1: Discovery
Parse input, analyze the seed idea, optionally explore codebase, establish session configuration.
Objective
- Generate session ID and create output directory
- Parse user input (text description or file reference)
- Analyze seed via Gemini CLI to extract problem space dimensions
- Conditionally explore codebase for existing patterns and constraints
- Gather user preferences (depth, focus areas) via interactive confirmation
- Write
spec-config.jsonas the session state file
Input
- Dependency:
$ARGUMENTS(user input from command) - Flags:
-y(auto mode),-c(continue mode)
Execution Steps
Step 1: Session Initialization
// Parse arguments
const args = $ARGUMENTS;
const autoMode = args.includes('-y') || args.includes('--yes');
const continueMode = args.includes('-c') || args.includes('--continue');
// Extract the idea/topic (remove flags)
const idea = args.replace(/(-y|--yes|-c|--continue)\s*/g, '').trim();
// Generate session ID
const slug = idea.toLowerCase()
.replace(/[^a-z0-9\u4e00-\u9fff]+/g, '-')
.replace(/^-|-$/g, '')
.slice(0, 40);
const date = new Date().toISOString().slice(0, 10);
const sessionId = `SPEC-${slug}-${date}`;
const workDir = `.workflow/.spec/${sessionId}`;
// Check for continue mode
if (continueMode) {
// Find existing session
const existingSessions = Glob('.workflow/.spec/SPEC-*/spec-config.json');
// If slug matches an existing session, load it and resume
// Read spec-config.json, find first incomplete phase, jump to that phase
return; // Resume logic handled by orchestrator
}
// Create output directory
Bash(`mkdir -p "${workDir}"`);
Step 2: Input Parsing
// Determine input type
if (idea.startsWith('@') || idea.endsWith('.md') || idea.endsWith('.txt')) {
// File reference - read and extract content
const filePath = idea.replace(/^@/, '');
const fileContent = Read(filePath);
// Use file content as the seed
inputType = 'file';
seedInput = fileContent;
} else {
// Direct text description
inputType = 'text';
seedInput = idea;
}
Step 3: Seed Analysis via Gemini CLI
Bash({
command: `ccw cli -p "PURPOSE: Analyze this seed idea/requirement to extract structured problem space dimensions.
Success: Clear problem statement, target users, domain identification, 3-5 exploration dimensions.
SEED INPUT:
${seedInput}
TASK:
- Extract a clear problem statement (what problem does this solve?)
- Identify target users (who benefits?)
- Determine the domain (technical, business, consumer, etc.)
- List constraints (budget, time, technical, regulatory)
- Generate 3-5 exploration dimensions (key areas to investigate)
- Assess complexity: simple (1-2 components), moderate (3-5 components), complex (6+ components)
MODE: analysis
EXPECTED: JSON output with fields: problem_statement, target_users[], domain, constraints[], dimensions[], complexity
CONSTRAINTS: Be specific and actionable, not vague
" --tool gemini --mode analysis`,
run_in_background: true
});
// Wait for CLI result before continuing
Parse the CLI output into structured seedAnalysis:
const seedAnalysis = {
problem_statement: "...",
target_users: ["..."],
domain: "...",
constraints: ["..."],
dimensions: ["..."]
};
const complexity = "moderate"; // from CLI output
Step 4: Codebase Exploration (Conditional)
// Detect if running inside a project with code
const hasCodebase = Glob('**/*.{ts,js,py,java,go,rs}').length > 0
|| Glob('package.json').length > 0
|| Glob('Cargo.toml').length > 0;
if (hasCodebase) {
Task({
subagent_type: "cli-explore-agent",
run_in_background: false,
description: `Explore codebase for spec: ${slug}`,
prompt: `
## Spec Generator Context
Topic: ${seedInput}
Dimensions: ${seedAnalysis.dimensions.join(', ')}
Session: ${workDir}
## MANDATORY FIRST STEPS
1. Search for code related to topic keywords
2. Read project config files (package.json, pyproject.toml, etc.) if they exist
## Exploration Focus
- Identify existing implementations related to the topic
- Find patterns that could inform architecture decisions
- Map current architecture constraints
- Locate integration points and dependencies
## Output
Write findings to: ${workDir}/discovery-context.json
Schema:
{
"relevant_files": [{"path": "...", "relevance": "high|medium|low", "rationale": "..."}],
"existing_patterns": ["pattern descriptions"],
"architecture_constraints": ["constraint descriptions"],
"integration_points": ["integration point descriptions"],
"tech_stack": {"languages": [], "frameworks": [], "databases": []},
"_metadata": { "exploration_type": "spec-discovery", "timestamp": "ISO8601" }
}
`
});
}
Step 5: User Confirmation (Interactive)
if (!autoMode) {
// Confirm problem statement and select depth
AskUserQuestion({
questions: [
{
question: `Problem statement: "${seedAnalysis.problem_statement}" - Is this accurate?`,
header: "Problem",
multiSelect: false,
options: [
{ label: "Accurate", description: "Proceed with this problem statement" },
{ label: "Needs adjustment", description: "I'll refine the problem statement" }
]
},
{
question: "What specification depth do you need?",
header: "Depth",
multiSelect: false,
options: [
{ label: "Light", description: "Quick overview - key decisions only" },
{ label: "Standard (Recommended)", description: "Balanced detail for most projects" },
{ label: "Comprehensive", description: "Maximum detail for complex/critical projects" }
]
},
{
question: "Which areas should we focus on?",
header: "Focus",
multiSelect: true,
options: seedAnalysis.dimensions.map(d => ({ label: d, description: `Explore ${d} in depth` }))
}
]
});
} else {
// Auto mode defaults
depth = "standard";
focusAreas = seedAnalysis.dimensions;
}
Step 6: Write spec-config.json
const specConfig = {
session_id: sessionId,
seed_input: seedInput,
input_type: inputType,
timestamp: new Date().toISOString(),
mode: autoMode ? "auto" : "interactive",
complexity: complexity,
depth: depth,
focus_areas: focusAreas,
seed_analysis: seedAnalysis,
has_codebase: hasCodebase,
phasesCompleted: [
{
phase: 1,
name: "discovery",
output_file: "spec-config.json",
completed_at: new Date().toISOString()
}
]
};
Write(`${workDir}/spec-config.json`, JSON.stringify(specConfig, null, 2));
Output
- File:
spec-config.json - File:
discovery-context.json(optional, if codebase detected) - Format: JSON
Quality Checklist
- Session ID matches
SPEC-{slug}-{date}format - Problem statement exists and is >= 20 characters
- Target users identified (>= 1)
- 3-5 exploration dimensions generated
- spec-config.json written with all required fields
- Output directory created
Next Phase
Proceed to Phase 2: Product Brief with the generated spec-config.json.