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 agentmods add skills/rohitg00/skillkit/task-decompositionnpx skills add rohitg00/skillkit --skill task-decompositiongit clone --depth 1 https://github.com/rohitg00/skillkitWhat 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 | $0.00108 | $0.01158 |
| Opus 5 | $0.00054 | $0.00579 |
| Sonnet 5 | $0.00022 | $0.00232 |
| Haiku 4.5 | $0.00011 | $0.00116 |
Grade A, and why
task-decomposition 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 yesterday.
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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Decomposition
You are breaking down a complex task into smaller, atomic units. Each unit should be independently completable and verifiable.
Core Principle
If a task feels too big, it is too big. Break it down until each piece is obvious.
A well-decomposed task should take no more than a few hours to complete and have a clear definition of done. Aim for tasks that are small, independent, testable, and clearly scoped.
Decomposition Techniques
1. Vertical Slicing
Break by user-visible functionality (each slice is deployable and testable independently):
Feature: User Registration
Slice 1: Email/password signup — form, validation, account creation
Slice 2: Email verification — send email, verify link, UI state
Slice 3: Social login (OAuth) — Google button, OAuth flow, account link
2. Horizontal Layering
Break by system layer:
Feature: Order Processing
Layer 1: Data Model — entities, migrations
Layer 2: Data Access — repository, CRUD, queries
Layer 3: Business Logic — service, validation rules
Layer 4: API Endpoints — routes, error handling
Layer 5: Frontend — form, API client, loading/error states
3. Workflow Decomposition
Break by process steps:
Task: Checkout flow
Step 1: Cart validation — stock check, quantities, totals
Step 2: Payment — collect details, validate, process
Step 3: Order creation — record, payment link, inventory update
Step 4: Confirmation — email, success page, invoice
4. Component Decomposition
Break by UI or system component:
Task: Dashboard page
Component 1: Header — logo, nav, user menu
Component 2: Stats cards — revenue, orders, customers
Component 3: Chart — sales trend, data fetch/transform
Component 4: Orders table — sort, pagination, row actions
For more detailed worked examples of each technique, see
EXAMPLES.md.
Task Template
For each decomposed task, define:
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.
- yesterday First seen · 172 lines · 108 tokens per session scan A 13592306938b
task-decomposition is a skill published in the GitHub repository rohitg00/skillkit (1,477 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 108 tokens to every session and 1,158 once invoked, about $0.0005 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 2026-08-30.
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