Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add curiositech/some_claude_skills --skill task-decomposergit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/curiositech/some_claude_skills/task-decomposer)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/task-decomposer"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/task-decomposer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/task-decomposer"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/task-decomposer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00125 | $0.01634 |
| Opus 5 | $0.00063 | $0.00817 |
| Sonnet 5 | $0.00025 | $0.00327 |
| Haiku 4.5 | $0.00013 | $0.00163 |
Grade A, and why
task-decomposer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 185 lines · 125 tokens per session scan A 06775028fcf5
task-decomposer is a skill published in the GitHub repository curiositech/some_claude_skills (221 stars, last pushed 5d ago), licensed MIT. It adds 125 tokens to every session and 1,634 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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