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 kevinnft/ai-agent-skills --skill planning-and-task-breakdowngit clone --depth 1 https://github.com/kevinnft/ai-agent-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/kevinnft/ai-agent-skills/planning-and-task-breakdown)<a href="https://agentmods.dev/skills/kevinnft/ai-agent-skills/planning-and-task-breakdown"><img src="https://agentmods.dev/badge/skills/kevinnft/ai-agent-skills/planning-and-task-breakdown/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/kevinnft/ai-agent-skills/planning-and-task-breakdown"><img src="https://agentmods.dev/badge/skills/kevinnft/ai-agent-skills/planning-and-task-breakdown.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 | $0.00056 | $0.01694 |
| Opus 5 | $0.00028 | $0.00847 |
| Sonnet 5 | $0.00011 | $0.00339 |
| Haiku 4.5 | $0.00006 | $0.00169 |
Grade A, and why
planning-and-task-breakdown 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 11d 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.
This is a copy
98% identical to planning-and-task-breakdown — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning and Task Breakdown
Overview
Decompose work into small, verifiable tasks with explicit acceptance criteria. Good task breakdown is the difference between an agent that completes work reliably and one that produces a tangled mess. Every task should be small enough to implement, test, and verify in a single focused session.
When to Use
- You have a spec and need to break it into implementable units
- A task feels too large or vague to start
- Work needs to be parallelized across multiple agents or sessions
- You need to communicate scope to a human
- The implementation order isn't obvious
When NOT to use: Single-file changes with obvious scope, or when the spec already contains well-defined tasks.
The Planning Process
Step 1: Enter Plan Mode
Before writing any code, operate in read-only mode:
- Read the spec and relevant codebase sections
- Identify existing patterns and conventions
- Map dependencies between components
- Note risks and unknowns
Do NOT write code during planning. The output is a plan document, not implementation.
Step 2: Identify the Dependency Graph
Map what depends on what:
Database schema
│
├── API models/types
│ │
│ ├── API endpoints
│ │ │
│ │ └── Frontend API client
│ │ │
│ │ └── UI components
│ │
│ └── Validation logic
│
└── Seed data / migrations
Implementation order follows the dependency graph bottom-up: build foundations first.
Step 3: Slice Vertically
Instead of building all the database, then all the API, then all the UI — build one complete feature path at a time:
Bad (horizontal slicing):
Task 1: Build entire database schema
Task 2: Build all API endpoints
Task 3: Build all UI components
Task 4: Connect everything
Good (vertical slicing):
Task 1: User can create an account (schema + API + UI for registration)
Task 2: User can log in (auth schema + API + UI for login)
Task 3: User can create a task (task schema + API + UI for creation)
Task 4: User can view task list (query + API + UI for list view)
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.
- 11d ago First seen · 229 lines · 56 tokens per session scan A 21e898e9e9d7
planning-and-task-breakdown is a skill published in the GitHub repository kevinnft/ai-agent-skills (14 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,694 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to planning-and-task-breakdown, differing in 5 lines, and is treated as a copy.
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