subagent-driven-development

subagent-driven-development is a skill for Claude Code, Codex from math-inc/OpenGauss. It costs 32 tokens per session (2,246 once invoked), scanned A, a copy of subagent-driven-development, MIT.

A way to carry out an implementation plan by assigning each independent task to a fresh coding helper, then checking the result for requirements and code quality.

In plain words
What is it for?
It helps split planned feature work into separate tasks, delegate them, and review each task in two stages.
Why use it?
It reduces confusion between tasks and catches missing requirements or quality problems before they spread.

Skill for Claude CodeCodex

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

Good fit It helps split planned feature work into separate tasks, delegate them, and review each task in two stages.

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Install with agentmods
npx agentmods add skills/math-inc/opengauss/subagent-driven-development
About the project

OpenGauss is a project-scoped Lean workflow orchestrator that gives coding agents a command-line interface for managing formal proof and formalization tasks. It is used with Lean projects to coordinate agents, tooling, backend sessions, and workflows supplied by lean4-skills. The catalogue add-ons operate these Gauss-native workflows.

math-inc/OpenGauss · 1,260 stars · on GitHub

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 math-inc/OpenGauss --skill subagent-driven-development
Clone the repo
git clone --depth 1 https://github.com/math-inc/OpenGauss

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 subagent-driven-development

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/math-inc/opengauss/subagent-driven-development"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/subagent-driven-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,246 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 80% 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 $0.00032 $0.02246
Opus 5 $0.00016 $0.01123
Sonnet 5 $0.00006 $0.00449
Haiku 4.5 $0.00003 $0.00225

Measured 6d ago against content hash 800b23902659, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

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 6d 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

80% identical to subagent-driven-development — 26 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 · 343 lines

How it starts

The opening of the file, as written. The whole thing — 343 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 · 343 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. 6d ago First seen · 343 lines · 32 tokens per session scan A 800b23902659

Subscribe to this mod's changes

subagent-driven-development is a skill published in the GitHub repository math-inc/OpenGauss (1,260 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 2,246 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to subagent-driven-development, differing in 26 lines, and is treated as a copy.

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