task-decomposer
Task Decomposer
Breaks natural-language problems into sub-tasks suitable for DAG nodes. The first step of the meta-DAG: before you can build or execute a DAG, you need to understand what the pieces are.
When to Use
✅ Use for:
- Breaking a vague problem into concrete sub-tasks
- Identifying phases, dependencies, and parallelization opportunities
- Determining which sub-tasks are concrete vs. vague (pluripotent)
- Selecting the appropriate domain meta-skill for decomposition
❌ NOT for:
- Building the DAG structure from sub-tasks (use
dag-planner) - Executing the tasks (use
dag-runtime) - Assigning skills to tasks (use
dag-skills-matcher)
Decomposition Process
flowchart TD
P[Problem description] --> M{Domain meta-skill available?}
M -->|Yes| L[Load meta-skill phase pattern]
M -->|No| R{Research needed?}
R -->|Yes| RA[Research standard decomposition]
R -->|No| Z[Zero-shot decomposition]
L --> D[Apply phase pattern to problem]
RA --> D
Z --> D
D --> C[Identify concrete sub-tasks]
D --> V[Identify vague/pluripotent sub-tasks]
D --> DEP[Map dependencies between sub-tasks]
D --> PAR[Identify parallelization opportunities]
C --> O[Ordered sub-task list with metadata]
V --> O
DEP --> O
PAR --> O
Step 1: Domain Detection
Classify the problem into a domain to select the right meta-skill:
| Domain Signals | Meta-Skill |
|---|---|
| "build", "implement", "code", "app", "website" | software-project-decomposition |
| "research", "analyze", "report", "synthesize" | research-synthesis-decomposition |
| "design", "UI", "wireframe", "prototype" | product-design-decomposition |
| "strategy", "market", "business", "revenue" | business-strategy-decomposition |
| "data", "model", "train", "predict" | ml-project-decomposition |
If no meta-skill matches, fall back to zero-shot decomposition.
Step 2: Phase Identification
Apply the meta-skill's phase pattern. Not all phases apply to every problem.
Decision: For each phase in the pattern, ask: "Does this problem need this phase?"
- Yes, and I can specify it now → Concrete sub-task
- Yes, but I can't specify it until prior phases complete → Vague/pluripotent node
- No → Skip this phase
Step 3: Sub-Task Specification
For each concrete sub-task:
sub_task:
id: unique-name
description: "What this sub-task produces (1-2 sentences)"
type: concrete | vague
depends_on: [upstream-sub-task-ids]
parallelizable_with: [sibling-sub-task-ids]
estimated_complexity: simple | moderate | complex
suggested_model_tier: 1 | 2 | 3
suggested_skills: [skill-names if known]
output_description: "What the output looks like"
For each vague/pluripotent sub-task:
sub_task:
id: unique-name
description: "What this phase will address (1-2 sentences)"
type: vague
depends_on: [upstream-sub-task-ids]
potential_paths:
- "Path A: [exciting possibility 1]"
- "Path B: [exciting possibility 2]"
- "Path C: [exciting possibility 3]"
expansion_trigger: on_upstream_complete
Step 4: Dependency Mapping
For each pair of sub-tasks, determine:
- Data dependency: Does B need A's output? → Edge from A to B
- Knowledge dependency: Does B need to know what A discovered? → Edge from A to B
- No dependency: A and B are independent → Parallelizable
Step 5: Output
Produce a structured decomposition:
decomposition:
problem: "original problem description"
domain: "detected domain"
meta_skill_used: "meta-skill name or 'zero-shot'"
phases:
- phase: 1
sub_tasks: [concrete tasks for this phase]
- phase: 2
sub_tasks: [mix of concrete and vague tasks]
total_concrete: 5
total_vague: 3
estimated_waves: 4
estimated_cost: "$0.08 - $0.25"
Decomposition Heuristics
Granularity
- Too fine: "Step 1: Open the file. Step 2: Read line 1." → Merge into one node
- Too coarse: "Step 1: Build the entire app." → Split into design, implement, test, deploy
- Right: Each sub-task is completable by one agent with 1-3 skills in one LLM call
Dependency Minimization
Fewer dependencies = more parallelism = faster execution. Prefer:
- Independent parallel tracks over long sequential chains
- Fan-out patterns (one source, many consumers) over daisy chains
- Late merging (combine results at the end, not incrementally)
Vagueness is OK
Don't force specificity where it doesn't exist yet. A vague node saying "Build the solution (details TBD after design phase)" is more honest and more useful than a fake-specific node that will be wrong.
Anti-Patterns
Premature Specificity
Wrong: Specifying exact implementation details for phases that depend on undone research. Right: Mark dependent phases as vague/pluripotent. Show potential paths.
Sequential Everything
Wrong: A linear chain of 10 tasks with no parallelism. Right: Look for independent tracks. Research and content writing can often happen in parallel.
Missing the Meta-Skill
Wrong: Decomposing a bridge design project like a software project. Right: Detect the domain, load the appropriate meta-skill, follow its phase pattern.