According to AlphaMoat, as of 2026-10, TaskMaster - AI Cost Optimizer has 7,911 downloads and 10 stars — ranked by downloads #3,513 among 10,914 AI skills in this ranking, and #468 of 1,632 in AI Agent.
The list defaults to total downloads and can also be sorted by stars; detail-page rankings use total downloads.
| Platform | Downloads | Stars | Comments |
|---|---|---|---|
| ClawHub ↗ | 3.9K | 8 | 3 |
| SkillHub ↗ | 7.9K | 10 | — |
Platforms count differently and update at different times.
It first judges task complexity, then assigns a model such as Haiku, Sonnet or Opus, spawns sub-agents in parallel where useful, and tracks token cost per task and for the whole project. The rule is not to spend a heavy model on simple work.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-10 | 7.9K | — | 10 |
| 2026-09 | 5.3K | — | 10 |
| 2026-08 | 4.7K | +28.0% | 10 |
| 2026-07 | 3.7K | +6.1% | 8 |
| 2026-06 | 3.4K | -19.0% | 8 |
| 2026-05 | 4.3K | — | 10 |
| 2026-03 | 3.6K | — | 8 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: taskmaster description: Project manager and task delegation system. Use when you need to break down complex work into smaller tasks, assign appropriate AI models based on complexity, spawn sub-agents for parallel execution, track progress, and manage token budgets. Ideal for research projects, multi-step workflows, or when you want to delegate routine tasks to cheaper models while handling complex coordination yourself. --- # TaskMaster: AI Project Manager & Task Delegation Transform complex projects into managed workflows with smart model selection and sub-agent orchestration. ## Core Capabilities
**🎯 Smart Task Triage** - Analyze complexity → assign appropriate model (Haiku/Sonnet/Opus) - Break large projects into smaller, manageable tasks - Prevent over-engineering (don't use Opus for simple web searches) **🤖 Sub-Agent Orchestration** - Spawn isolated sub-agents with specific model constraints - Run tasks in parallel for faster completion - Consolidate results into coherent deliverables **💰 Budget Management** - Track token costs per task and total project - Set budget limits to prevent runaway spending - Optimize model selection for cost-efficiency **📊 Progress Tracking** - Real-time status of all active tasks - Failed task retry with escalation - Final deliverable compilation ## Quick Start ### 1. Basic Task Delegation ```markdown TaskMaster: Research PDF processing libraries - Budget: $2.00 - Priority: medium - Deadline: 2 hours ``` ### 2. Complex Project Breakdown ```markdown TaskMaster: Build recipe app MVP - Components: UI mockup, backend API, data schema, deployment - Budget: $15.00 - Timeline: 1 week - Auto-assign models based on complexity ``` ## Model Selection Rules **Haiku ($0.25/$1.25)** - Simple, repetitive tasks: - Web searches & summarization - Data formatting & extraction - Basic file operations - Status checks & monitoring **Sonnet ($3/$15)** - Most development work: - Research & analysis - Code writing & debugging - Documentation creation - Technical design **Opus ($15/$75)** - Complex reasoning: - Architecture decisions - Creative problem-solving - Code reviews & optimization - Strategic planning ## Advanced Usage ### Custom Model Assignment Override automatic selection when you know better: ```markdown TaskMaster: Debug complex algorithm [FORCE: Opus] ``` ### Parallel Execution Run multiple tasks simultaneously: ```markdown TaskMaster: Multi-research project - Task A: Library comparison - Task B: Performance benchmarks - Task C: Security analysis [PARALLEL: true] ``` ### Budget Controls Set spending limits: ```markdown TaskMaster: Market research - Max budget: $5.00 - Escalate if >$3.00 spent - Stop if any single task >$1.00 ``` ## Key Resources - **Model Selection**: See [references/model-selection-rules.md](references/model-selection-rules.md) for detailed complexity guidelines - **Task Templates**: See [references/task-templates.md](references/task-templates.md) for common task patterns - **Delegation Engine**: Uses `scripts/delegate_task.py` for core orchestration logic ## Implementation Notes **Sessions Management**: Each sub-agent gets isolated session with specific model constraints. No cross-talk unless explicitly designed. **Error Handling**: Failed tasks automatically retry once on Sonnet, then escalate to human review. **Result Aggregation**: TaskMaster compiles all sub-agent results into a single, coherent deliverable for the user. **Token Tracking**: Real-time cost monitoring with alerts when approaching budget limits.
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Data as of 2026-10. Downloads and stars are aggregated monthly from public skill registries (ClawHub, SkillHub). See data methodology.