Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Subagent Driven Development

ASecurity

Use when executing an implementation plan composed of independent tasks in the current session. Dispatch a fresh subagent per task and run a two-stage review after each task: spec compliance, then code quality.

15 stars
0 votes
0 copies
0 views
Added 9/28/2026
ai-agentspythondebuggingcode-reviewgit

Security Analysis

A100/100

Scanned 9/28/2026

Install to Claude Code

$npx -y skills add AidALL/ghost-alice --skill subagent-driven-development --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Subagent Driven Development?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Subagent Driven Development
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/aidall-subagent-driven-development/badge)](https://www.skillsdirectory.com/skills/aidall-subagent-driven-development)

More formats (shields.io, HTML) on the badges page.

Files
SKILL.md
---
name: subagent-driven-development
description: "Use when executing an implementation plan composed of independent tasks in the current session. Dispatch a fresh subagent per task and run a two-stage review after each task: spec compliance, then code quality."
compatibility:
  - "Python 3.11+ standard library"
---

# Subagent-Driven Development

Dispatch a fresh subagent per task to execute the plan. After every task, run a two-stage review: spec compliance review first, then code quality review.

○ Why subagents

Delegate each task to a specialized agent with an isolated context. Make the instructions and context precise so the agent stays focused on the task and succeeds. The agent must never inherit your session's context or history. You construct exactly what the agent needs. This also preserves your own context for coordination work.

○ Core principle

A fresh subagent per task plus a two-stage review (spec then quality) supports focused work and faster correction.
## Contents

- [When to Use](#when-to-use)
- [Procedure](#procedure)
- [Model Selection](#model-selection)
- [Handling Implementer States](#handling-implementer-states)
- [Prompt Templates](#prompt-templates)
- [Example Workflow](#example-workflow)
- [Benefits](#benefits)
- [Red Flags](#red-flags)
- [Integration](#integration)


## When to Use

```dot
digraph when_to_use {
    "Is there an implementation plan?" [shape=diamond];
    "Are the tasks mostly independent?" [shape=diamond];
    "Staying in this session?" [shape=diamond];
    "subagent-driven-development" [shape=box];
    "executing-plans" [shape=box];
    "Manual execution or brainstorm first" [shape=box];

    "Is there an implementation plan?" -> "Are the tasks mostly independent?" [label="yes"];
    "Is there an implementation plan?" -> "Manual execution or brainstorm first" [label="no"];
    "Are the tasks mostly independent?" -> "Staying in this session?" [label="yes"];
    "Are the tasks mostly independent?" -> "Manual execution or brainstorm first" [label="no - tightly coupled"];
    "Staying in this session?" -> "subagent-driven-development" [label="yes"];
    "Staying in this session?" -> "executing-plans" [label="no - parallel session"];
}
```

□ Difference from executing-plans (parallel session)

- Same session (no context switch)
- A fresh subagent per task (no context contamination)
- A two-stage review after every task: spec compliance first, then code quality
- Faster iteration (no human intervention between tasks)

## Procedure

```dot
digraph process {
    rankdir=TB;

    subgraph cluster_per_task {
        label="Per task";
        "Dispatch implementer subagent (./implementer-prompt.md)" [shape=box];
        "Does the implementer ask a question?" [shape=diamond];
        "Answer the question, provide context" [shape=box];
        "Implementer implements, tests, commits, self-reviews" [shape=box];
        "Dispatch spec reviewer (./spec-reviewer-prompt.md)" [shape=box];
        "Does the spec reviewer confirm a spec match?" [shape=diamond];
        "Implementer fixes spec gaps" [shape=box];
        "Dispatch code quality reviewer (./code-quality-reviewer-prompt.md)" [shape=box];
        "Does the code quality reviewer approve?" [shape=diamond];
        "Implementer fixes quality issues" [shape=box];
        "Mark the task done in TodoWrite" [shape=box];
    }

    "Read the plan, extract the full text of every task, note the context, create TodoWrite" [shape=box];
    "Any tasks left?" [shape=diamond];
    "Dispatch a final code reviewer over the whole implementation" [shape=box];
    "Use finishing-a-development-branch" [shape=box style=filled fillcolor=lightgreen];

    "Read the plan, extract the full text of every task, note the context, create TodoWrite" -> "Dispatch implementer subagent (./implementer-prompt.md)";
    "Dispatch implementer subagent (./implementer-prompt.md)" -> "Does the implementer ask a question?";
    "Does the implementer ask a question?" -> "Answer the question, provide context" [label="yes"];
    "Answer the question, provide context" -> "Dispatch implementer subagent (./implementer-prompt.md)";
    "Does the implementer ask a question?" -> "Implementer implements, tests, commits, self-reviews" [label="no"];
    "Implementer implements, tests, commits, self-reviews" -> "Dispatch spec reviewer (./spec-reviewer-prompt.md)";
    "Dispatch spec reviewer (./spec-reviewer-prompt.md)" -> "Does the spec reviewer confirm a spec match?";
    "Does the spec reviewer confirm a spec match?" -> "Implementer fixes spec gaps" [label="no"];
    "Implementer fixes spec gaps" -> "Dispatch spec reviewer (./spec-reviewer-prompt.md)" [label="re-review"];
    "Does the spec reviewer confirm a spec match?" -> "Dispatch code quality reviewer (./code-quality-reviewer-prompt.md)" [label="yes"];
    "Dispatch code quality reviewer (./code-quality-reviewer-prompt.md)" -> "Does the code quality reviewer approve?";
    "Does the code quality reviewer approve?" -> "Implementer fixes quality issues" [label="no"];
    "Implementer fixes quality issues" -> "Dispatch code quality reviewer (./code-quality-reviewer-prompt.md)" [label="re-review"];
    "Does the code quality reviewer approve?" -> "Mark the task done in TodoWrite" [label="yes"];
    "Mark the task done in TodoWrite" -> "Any tasks left?";
    "Any tasks left?" -> "Dispatch implementer subagent (./implementer-prompt.md)" [label="yes"];
    "Any tasks left?" -> "Dispatch a final code reviewer over the whole implementation" [label="no"];
    "Dispatch a final code reviewer over the whole implementation" -> "Use finishing-a-development-branch";
}
```

## Model Selection

To save cost and improve speed, use the weakest model that can handle each role.

□ Mechanical implementation work (isolated function, clear spec, 1-2 files)

Use a fast, cheap model. When the plan is well specified, most implementation work is mechanical.

□ Integration and judgment work (multi-file coordination, pattern matching, debugging)

Use the standard model.

□ Architecture, design, and review work

Use the strongest available model.

□ Task complexity signals

- A complete spec in 1-2 files → low-cost model
- Multiple files with integration concerns → standard model
- Design judgment or broad codebase understanding required → strongest model

## Handling Implementer States

The implementer subagent reports one of four states. Handle each appropriately.

□ DONE

Proceed to the spec compliance review.

□ DONE_WITH_CONCERNS

The implementer finished the task but flagged a doubt. Read the concern before proceeding. If the concern is about correctness or scope, address it before the review. If it is an observation (for example, "this file is growing"), note it and proceed to the review.

□ NEEDS_CONTEXT

The implementer needs information that was not provided. Provide the missing context and redispatch.

□ BLOCKED

The implementer cannot complete the task. Assess the blocking factor.

- If it is a context problem, give more context and redispatch with the same model
- If more reasoning is needed, redispatch with a stronger model
- If the task is too large, split it into smaller pieces
- If the plan itself is wrong, escalate to a human

Never ignore an escalation or make the same model retry without any change. When the implementer says it is blocked, something must change.

## Prompt Templates

Use the templates in the `references/` directory.

- `references/implementer-prompt.md`: dispatch the implementer subagent.
- `references/spec-reviewer-prompt.md`: dispatch the spec compliance reviewer subagent.
- `references/code-quality-reviewer-prompt.md`: dispatch the code quality reviewer subagent.

## Example Workflow

For a full end-to-end example, use `references/example-workflow.md`.

Core sequence:

- Read the plan file only once at the start, and extract all task text and the shared context first.
- For each Task, proceed in the order implementer → spec compliance reviewer → code quality reviewer.
- When a review surfaces a missing, extra, or quality issue, hand it back to the implementer and re-run the same review stage.
- After all Tasks, dispatch a final code-reviewer one more time.

## Benefits

□ Versus manual execution

- Subagents can be instructed to follow TDD
- Fresh context per task (no confusion)
- Parallel-safe (no interference between subagents)
- Subagents can ask questions (both before and during a task)

□ Versus Executing Plans

- Same session (no handoff)
- Continuous progress (no waiting)
- Required review checkpoints

□ Efficiency gains

- No file-reading overhead (the controller provides the full text)
- The controller curates exactly the context needed
- The subagent receives complete information from the start
- Questions surface before the task (not after the fact)

□ Quality gates

- Self-review catches issues before handoff
- A two-stage review: spec compliance, then code quality
- The review loop ensures fixes actually work
- Spec compliance prevents over- and under-building
- Code quality ensures it is well built

□ Costs

- More subagent calls (an implementer plus two reviewers per task)
- More preparation work for the controller (extract all tasks up front)
- The review loop adds iterations
- But it catches issues early (cheaper than debugging after the fact)

## Red Flags

□ Never do this

- Starting implementation on the main or master branch without the user's explicit consent
- Skipping a review (spec compliance or code quality)
- Proceeding with unfixed issues
- Dispatching multiple implementer subagents in parallel (conflicts)
- Letting a subagent read the plan file (you provide the full text)
- Skipping scene-setting context (the subagent must understand where the task sits)
- Ignoring a subagent's question (answer it before letting it proceed)
- Accepting "close enough" on spec compliance (a spec reviewer finding an issue = not done)
- Skipping the review loop (reviewer finds an issue = implementer fixes = re-review)
- Letting the implementer's self-review replace the actual review (both are needed)
- Starting the code quality review before spec compliance is ✅ (wrong order)
- Moving to the next task while either review still has an unresolved issue

□ When a subagent asks a question

- Answer clearly and completely
- Provide extra context if needed
- Do not push it into implementation

□ When a reviewer finds an issue

- The implementer (the same subagent) fixes it
- The reviewer reviews again
- Repeat until approval
- Do not skip the re-review

□ When a subagent fails a task

- Dispatch a fixing subagent with specific instructions
- Do not fix it manually (context contamination)

## Integration

□ Required workflow skills

- `using-git-worktrees`: set up an isolated workspace before starting (required).
- `writing-plans`: produces the plan that this skill executes.
- `requesting-code-review`: the code review template for the reviewer subagents.
- `finishing-a-development-branch`: close out development after all tasks are done.

□ Subagents must use

- `test-driven-development` means the subagent follows TDD on each task.

□ Alternative workflow

- `executing-plans`: for parallel sessions instead of same-session execution.

Attribution

AidALLAidALL
View sourceMore from AidALL →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".

1074701 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

695601 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3351 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

691 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →