task-decomposer

task-decomposer is a skill for Claude Code from aldianriski/lean-flow. It costs 79 tokens per session (2,624 once invoked), scanned A, original, MIT.

A planning skill that turns a feature request, ticket, product requirements document, or epic into structured `TASK-NNN` entries in `TODO.md`. It records assumptions, risks, and vertical slices, meaning small end-to-end pieces of work.

In plain words
What is it for?
Use it to break down new features, tickets, PRDs, and larger epics into actionable tasks with acceptance details and validation.
Why use it?
It turns vague or oversized requests into a checked scope that developers can implement step by step.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the lean-flow plugin — 16 skills shipped together

Install

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.

agentmods
npx agentmods add skills/aldianriski/lean-flow/task-decomposer
Any agent
npx skills add aldianriski/lean-flow --skill task-decomposer
Clone the repo
git clone --depth 1 https://github.com/aldianriski/lean-flow

Made for: Claude Code.

Or install lean-flow, the plugin that ships this one along with the rest of its 16 skills.

Wrote 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.

agentmods badge for task-decomposer

README.md
[![agentmods](https://agentmods.dev/badge/skills/aldianriski/lean-flow/task-decomposer.svg)](https://agentmods.dev/skills/aldianriski/lean-flow/task-decomposer)
Your own site
<a href="https://agentmods.dev/skills/aldianriski/lean-flow/task-decomposer"><img src="https://agentmods.dev/badge/skills/aldianriski/lean-flow/task-decomposer.svg" alt="Measured on agentmods" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,624 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.02624
Opus 5 $0.00039 $0.01312
Sonnet 5 $0.00016 $0.00525
Haiku 4.5 $0.00008 $0.00262

Measured 5d ago against content hash d955e15607f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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 5d 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.

skills/task-decomposer/SKILL.md · 115 lines

How it starts

The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Task Decomposer

Translate any form of human intent into fully-formed TASK-NNN entries. The approved output serves as the scope gate — /orchestrator G1 then runs as a fast-path confirm (scope unchanged?), not a re-grill.

Input types

Input Detection
Freeform — "add Google OAuth login" no URL, no -- flag
Ticket — JIRA-123 or a Linear/GitHub URL matches [A-Z]+-[0-9]+ or a URL
PRD — --prd docs/feature.md --prd flag + path
Epic — --epic "Payments" or --epic EPIC-003 --epic flag + name or id

For a ticket, fetch the description first (ask the user to paste if credentials are missing — never block on env vars). For an epic, resolve the flag to docs/epic/EPIC-NNN-<slug>.md (match on id, else slug, else the INDEX.md row) and read it before grilling. Check docs/epic/archive/ before concluding it does not exist — a closed epic is archived there (§11) and resolving only the live directory would report a finished epic as never-created, sending the owner to /lean-doc-generator epic to re-open work that is already done. A match in archive/ is a closed epic: say so, and note that new work toward that outcome opens a new epic rather than reopening this one — its Outcome, Scope-Out and Open questions are already-settled context, so re-asking them is the interview a resolved epic exists to prevent. Decompose only the slice the owner names, never the whole epic at once: an epic spans sprints by definition, and a Plan holds ~12 tasks. No epic doc for that name → it is not an epic yet; say so and offer /lean-doc-generator epic (nameable outcome) or --fog (not yet nameable). Never create the epic here — creation is the generator's job; this skill consumes.

Procedure

  1. Clarify — the grill (freeform / ticket only) — ambiguity is cheapest to kill at intake. Decisions form a dependency tree; work it in rounds by frontier. The frontier is every decision whose prerequisites are already settled — ask all of it at once as one AskUserQuestion popup (each option with a recommended answer), then recompute the frontier from the answers. The discriminator is dependency, not count: batching dependent questions is what produces vague answers, because the user must guess at inputs they have not given yet; batching independent ones costs nothing and saves a round-trip. Stop when the frontier is empty — every branch visited, nothing silently assumed. Finding facts is your job, never the user's: an unresolved fact is a prerequisite in the tree, not a question — resolve it yourself (for mature / unfamiliar code, recon via the Explore agent — existing impl + tests + deps → a tight brief in its own context, a cheap-tier sonnet pass; the grill itself stays on the session model. Tier map → CONTEXT.md). Only the branch downstream of an open exploration waits; the rest of the frontier proceeds. Moves:
    • Challenge the glossary — a term conflicts with CONTEXT.md? Surface it: "your glossary says X, you seem to mean Y — which?"
    • Sharpen fuzzy language — replace an overloaded word ("account", "user") with a precise canonical term; feed a newly-pinned term straight to /lean-doc-generator (glossary), don't batch.
    • Invent edge-case scenarios — concrete cases that force the boundaries between concepts to be made explicit.
    • Cross-reference code — a claim contradicts the code? Surface the contradiction.
    • A design that must be felt, or a high-stakes fork — don't resolve it here: record it on the task (assumes:) so G2 routes to /prototype / /council.

Read the full file on GitHub · 115 lines

Files

What ships with it

2 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.

Changes

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.

  1. 5d ago First seen · 115 lines · 79 tokens per session scan A d955e15607f9

Subscribe to this mod's changes

task-decomposer is a skill published in the GitHub repository aldianriski/lean-flow (5 stars, last pushed 6d ago), licensed MIT. It adds 79 tokens to every session and 2,624 once invoked, about $0.0004 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 2026-08-31.

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