Some_claude_skills task-decomposer
Breaks natural-language problem descriptions into sub-tasks suitable for DAG nodes. The entry point of the meta-DAG. Identifies phases, dependencies, parallelization opportunities, and vague/pluripotent
git clone https://github.com/curiositech/some_claude_skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/curiositech/some_claude_skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/task-decomposer" ~/.claude/skills/curiositech-some-claude-skills-task-decomposer && rm -rf "$T"
.claude/skills/task-decomposer/SKILL.mdTask 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" | |
| "research", "analyze", "report", "synthesize" | |
| "design", "UI", "wireframe", "prototype" | |
| "strategy", "market", "business", "revenue" | |
| "data", "model", "train", "predict" | |
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.