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review-tasks-decomposition

review-tasks-decomposition is a skill for Claude Code, Codex from tomzx/agents. It costs 23 tokens per session (981 once invoked), scanned A, original, MIT.

A review tool for breaking a software feature into individual development tasks.

In plain words
What is it for?
Checking task files and plans for coverage, dependencies, granularity, and implementation readiness.
Why use it?
It identifies tasks that are too large, incomplete, poorly ordered, hard to estimate, or missing clear acceptance criteria.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 6repo yesterday A scan 23 tokens original MIT

Good fit Checking task files and plans for coverage, dependencies, granularity, and implementation readiness.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tomzx/agents/review-tasks-decomposition
View source ↗ tomzx/agents
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.

Any agent
npx skills add tomzx/agents --skill review-tasks-decomposition
Clone the repo
git clone --depth 1 https://github.com/tomzx/agents

Made for: Claude Code, Codex.

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.

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README.md
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Your own site
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Your own site · 80×15
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Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 981 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00023 $0.00981
Opus 5 $0.00012 $0.00491
Sonnet 5 $0.00005 $0.00196
Haiku 4.5 $0.00002 $0.00098

Measured 7d ago against content hash 846ffc4553f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

review-tasks-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 7d 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/review-tasks-decomposition/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Tasks Decomposition

Audits a task decomposition and reports findings across five categories: granularity, completeness, dependencies, acceptance criteria, and estimability.

Prerequisites

  • Apply the shared SDLC conventions in skills/sdlc/references/shared.md.
  • If no argument is provided, locate the feature directory under .sdlc/features/ whose frontmatter issue field references $ISSUE_NUMBER.
  • .sdlc/features/N-<slug>/tasks/ directory containing individual task files, or task files provided in context
  • .sdlc/features/N-<slug>/plan.md (optional, improves completeness check)

Steps

  1. Read all .md files in .sdlc/features/N-<slug>/tasks/.
  2. Evaluate each task against the checklist below.
  3. Report findings by category. Omit categories with no findings.
  4. Write the findings to .sdlc/features/N-<slug>/review-tasks.md with frontmatter artifact: tasks, verdict (approved if there are no blocking findings, changes-requested if the author must address findings, rejected for a fundamental flaw), and reviewed_at: <ISO date>, and the findings as the body, per skills/sdlc/references/shared.md. Record any unresolved open questions in the findings body. For any question that carries meaningful risk to the implementation, also invoke /create-assumption to record it formally. When the verdict is approved, set each task file's frontmatter status to pending (the task-lifecycle "ready to start" state, which create-implementation relies on).
  5. Populate the Task Progress table in .sdlc/features/N-<slug>/progress.md with all tasks, their sizes, and pending status. Set re_entry_point: "tests" and current_phase: "tasks-complete" in the frontmatter.

Review Checklist

Granularity

  • Are any tasks too large to complete in one session (> 2 days)?
  • Are any tasks too small and should be merged with adjacent work?
  • Is each task independently deliverable?

Completeness

  • Do the tasks collectively cover all plan phases and deliverables?
  • Are setup, teardown, and operational tasks included (migrations, feature flags, monitoring)?
  • Are documentation and testing tasks explicitly listed?

Read the full file on GitHub · 110 lines

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. 7d ago First seen · 110 lines · 23 tokens per session scan A 846ffc4553f2

Subscribe to this mod's changes

review-tasks-decomposition is a skill published in the GitHub repository tomzx/agents (6 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 981 once invoked, about $0.0001 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.

PlanningProject management
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