dev-subagent-driven-development

dev-subagent-driven-development is a skill for Claude Code, Codex from kevinnft/ai-agent-skills. It costs 18 tokens per session (2,460 once invoked), scanned A, a copy of subagent-driven-development, MIT.

A workflow for having separate helper agents implement tasks from a plan and review the work in two stages.

In plain words
What is it for?
It helps split a plan into tasks, delegate them, check whether each meets the specification, and review the implementation quality.
Why use it?
Fresh agents and intermediate reviews can reveal missed requirements or quality problems earlier.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit It helps split a plan into tasks, delegate them, check whether each meets the specification, and review the implementation quality.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kevinnft/ai-agent-skills/subagent-driven-development
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 kevinnft/ai-agent-skills --skill subagent-driven-development
Clone the repo
git clone --depth 1 https://github.com/kevinnft/ai-agent-skills

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.

agentmods badge for dev-subagent-driven-development

README.md
[![agentmods](https://agentmods.dev/badge/skills/kevinnft/ai-agent-skills/subagent-driven-development/github.svg)](https://agentmods.dev/skills/kevinnft/ai-agent-skills/subagent-driven-development)
Your own site
<a href="https://agentmods.dev/skills/kevinnft/ai-agent-skills/subagent-driven-development"><img src="https://agentmods.dev/badge/skills/kevinnft/ai-agent-skills/subagent-driven-development/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.

agentmods 80×15 button for dev-subagent-driven-development

Your own site · 80×15
<a href="https://agentmods.dev/skills/kevinnft/ai-agent-skills/subagent-driven-development"><img src="https://agentmods.dev/badge/skills/kevinnft/ai-agent-skills/subagent-driven-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,460 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 86% copy Near-identical to another mod 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 $0.00018 $0.02460
Opus 5 $0.00009 $0.01230
Sonnet 5 $0.00004 $0.00492
Haiku 4.5 $0.00002 $0.00246

Measured 9d ago against content hash be73f35300b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

dev-subagent-driven-development 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.

Origin

This is a copy

86% identical to subagent-driven-development — 18 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.

skills/software-development/subagent-driven-development/SKILL.md · 357 lines

How it starts

The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Subagent-Driven Development

Overview

Execute implementation plans by dispatching fresh subagents per task with systematic two-stage review.

Core principle: Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.

When to Use

Use this skill when:

  • You have an implementation plan (from writing-plans skill or user requirements)
  • Tasks are mostly independent
  • Quality and spec compliance are important
  • You want automated review between tasks

vs. manual execution:

  • Fresh context per task (no confusion from accumulated state)
  • Automated review process catches issues early
  • Consistent quality checks across all tasks
  • Subagents can ask questions before starting work

The Process

1. Read and Parse Plan

Read the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:

# Read the plan
read_file("docs/plans/feature-plan.md")

# Create todo list with all tasks
todo([
    {"id": "task-1", "content": "Create User model with email field", "status": "pending"},
    {"id": "task-2", "content": "Add password hashing utility", "status": "pending"},
    {"id": "task-3", "content": "Create login endpoint", "status": "pending"},
])

Key: Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.

2. Per-Task Workflow

For EACH task in the plan:

Step 1: Dispatch Implementer Subagent

Use delegate_task with complete context:

delegate_task(
    goal="Implement Task 1: Create User model with email and password_hash fields",
    context="""
    TASK FROM PLAN:
    - Create: src/models/user.py
    - Add User class with email (str) and password_hash (str) fields
    - Use bcrypt for password hashing
    - Include __repr__ for debugging

    FOLLOW TDD:
    1. Write failing test in tests/models/test_user.py
    2. Run: pytest tests/models/test_user.py -v (verify FAIL)
    3. Write minimal implementation
    4. Run: pytest tests/models/test_user.py -v (verify PASS)
    5. Run: pytest tests/ -q (verify no regressions)
    6. Commit: git add -A && git commit -m "feat: add User model with password hashing"

    PROJECT CONTEXT:
    - Python 3.11, Flask app in src/app.py
    - Existing models in src/models/
    - Tests use pytest, run from project root
    - bcrypt already in requirements.txt
    """,
    toolsets=['terminal', 'file']
)

Read the full file on GitHub · 357 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. 9d ago First seen · 357 lines · 18 tokens per session scan A be73f35300b1

Subscribe to this mod's changes

dev-subagent-driven-development is a skill published in the GitHub repository kevinnft/ai-agent-skills (14 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 2,460 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to subagent-driven-development, differing in 18 lines, and is treated as a copy.

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