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 malue-ai/dazee-small --skill planning-taskgit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/planning-task)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/planning-task"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/planning-task/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/malue-ai/dazee-small/planning-task"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/planning-task.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00046 | $0.01336 |
| Opus 5 | $0.00023 | $0.00668 |
| Sonnet 5 | $0.00009 | $0.00267 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
planning-task 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 9d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Planning Skill
Breaks down complex user requests into structured, trackable task plans with dependencies.
When to Use
Load this skill when:
- User has a multi-step request (e.g., "制作产品PPT需要市场数据")
- Need to organize work into phases/steps
- User mentions: "plan", "tasks", "steps", "breakdown", "organize"
- Complex deliverable requiring coordination
Capabilities
- Task Decomposition: Break complex goals into atomic tasks
- Dependency Management: Identify which tasks must complete before others
- Progress Tracking: Generate plan.json and todo.md for monitoring
- Format Generation: Create both machine-readable (JSON) and human-readable (Markdown) formats
Workflow
Phase 1: Analyze User Intent
Understand the goal and identify key deliverables:
# Use code_execution to analyze
user_intent = "制作AI产品介绍PPT,包含市场数据"
# Identify components
components = [
"搜索市场数据",
"分析竞品信息",
"设计PPT结构",
"生成SlideSpeak配置",
"验证配置",
"渲染PPT"
]
Phase 2: Generate Structured Plan
Use the helper script to create plan.json:
# Load and execute the plan generator
with open('skills/library/planning-task/scripts/generate_plan.py', 'r') as f:
exec(f.read())
plan = generate_task_plan(
user_intent="制作AI产品介绍PPT,包含市场数据",
tasks=[
{"id": "task_001", "description": "搜索AI客服市场数据", "dependencies": []},
{"id": "task_002", "description": "生成PPT配置", "dependencies": ["task_001"]},
{"id": "task_003", "description": "渲染PPT", "dependencies": ["task_002"]}
]
)
# Save plan.json
import json
with open('workspace/plan.json', 'w') as f:
json.dump(plan, f, ensure_ascii=False, indent=2)
Phase 3: Generate Human-Readable Todo
Create todo.md for user visibility:
# Load and execute the todo generator
with open('skills/library/planning-task/scripts/generate_todo.py', 'r') as f:
exec(f.read())
todo_markdown = generate_todo_markdown(plan)
# Save todo.md
with open('workspace/todo.md', 'w') as f:
f.write(todo_markdown)
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 183 lines · 46 tokens per session scan A 3b834c5495d6
planning-task is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 46 tokens to every session and 1,336 once invoked, about $0.0002 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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