Subagent Driven Development

Subagent-Driven Development

Execute plan by dispatching a fresh implementer subagent per task, a task review (spec compliance + code quality) after each, and a broad whole-branch review at the end.

Why subagents: You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

Core principle: Fresh subagent per task + task review (spec + quality) + broad final review = high quality, fast iteration

Narration: between tool calls, narrate at most one short line — the ledger and the tool results carry the record.

Continuous execution: Do not pause to check in with your human partner between tasks. Execute all tasks from the plan without stopping. The only reasons to stop are: BLOCKED status you cannot resolve, ambiguity that genuinely prevents progress, or all tasks complete. "Should I continue?" prompts and progress summaries waste their time — they asked you to execute the plan, so execute it.

When to Use

digraph when_to_use {
    "Have implementation plan?" [shape=diamond];
    "Tasks mostly independent?" [shape=diamond];
    "Stay in this session?" [shape=diamond];
    "subagent-driven-development" [shape=box];
    "executing-plans" [shape=box];
    "Manual execution or brainstorm first" [shape=box];

    "Have implementation plan?" -> "Tasks mostly independent?" [label="yes"];
    "Have implementation plan?" -> "Manual execution or brainstorm first" [label="no"];
    "Tasks mostly independent?" -> "Stay in this session?" [label="yes"];
    "Tasks mostly independent?" -> "Manual execution or brainstorm first" [label="no - tightly coupled"];
    "Stay in this session?" -> "subagent-driven-development" [label="yes"];
    "Stay in this session?" -> "executing-plans" [label="no - parallel session"];
}

vs. Executing Plans (parallel session):

• Same session (no context switch)
• Fresh subagent per task (no context pollution)
• Review after each task (spec compliance + code quality), broad review at the end
• Faster iteration (no human-in-loop between tasks)

The Process

digraph process {
    rankdir=TB;

    subgraph cluster_per_task {
        label="Per Task";
        "Dispatch implementer subagent (./implementer-prompt.md)" [shape=box];
        "Implementer asks questions?" [shape=diamond];
        "Answer questions, provide context" [shape=box];
        "Implementer implements, tests, commits, self-reviews" [shape=box];
        "Generate review package, dispatch task reviewer (./task-reviewer-prompt.md)" [shape=box];
        "Spec ✅ and quality approved?" [shape=diamond];
        "Finding conflicts with plan text?" [shape=diamond];
        "Ask human partner which governs" [shape=box];
        "Fix round R of 5: R≤3 resume implementer; R≥4 fresh implementer, more capable model" [shape=box];
        "Dispatch scoped re-review (./re-review-prompt.md)" [shape=box];
        "All findings addressed?" [shape=diamond];
        "R = 5?" [shape=diamond];
        "Adjudicate each open finding" [shape=box];
        "Any load-bearing finding?" [shape=diamond];
        "STOP: report BLOCKED to human partner" [shape=box];
        "Park findings in ledger with rulings" [shape=box];
        "Append completion to ledger, mark todo complete" [shape=box];
    }

    "Setup: worktree, ledger check, read plan, pre-flight review" [shape=box];
    "More tasks remain?" [shape=diamond];
    "Dispatch final code reviewer (../requesting-code-review/code-reviewer.md)" [shape=box];
    "Final findings? ONE fix dispatch, one scoped re-review, adjudicate residuals" [shape=box];
    "Final review clean: delete this plan's workspace" [shape=box];
    "Use superpowers-brain:finishing-a-development-branch" [shape=box style=filled fillcolor=lightgreen];

    "Setup: worktree, ledger check, read plan, pre-flight review" -> "Dispatch implementer subagent (./implementer-prompt.md)";
    "Dispatch implementer subagent (./implementer-prompt.md)" -> "Implementer asks questions?";
    "Implementer asks questions?" -> "Answer questions, provide context" [label="yes"];
    "Answer questions, provide context" -> "Implementer implements, tests, commits, self-reviews";
    "Implementer asks questions?" -> "Implementer implements, tests, commits, self-reviews" [label="no"];
    "Implementer implements, tests, commits, self-reviews" -> "Generate review package, dispatch task reviewer (./task-reviewer-prompt.md)";
    "Generate review package, dispatch task reviewer (./task-reviewer-prompt.md)" -> "Spec ✅ and quality approved?";
    "Spec ✅ and quality approved?" -> "Append completion to ledger, mark todo complete" [label="yes"];
    "Spec ✅ and quality approved?" -> "Finding conflicts with plan text?" [label="no"];
    "Finding conflicts with plan text?" -> "Ask human partner which governs" [label="yes"];
    "Ask human partner which governs" -> "Fix round R of 5: R≤3 resume implementer; R≥4 fresh implementer, more capable model";
    "Finding conflicts with plan text?" -> "Fix round R of 5: R≤3 resume implementer; R≥4 fresh implementer, more capable model" [label="no"];
    "Fix round R of 5: R≤3 resume implementer; R≥4 fresh implementer, more capable model" -> "Dispatch scoped re-review (./re-review-prompt.md)";
    "Dispatch scoped re-review (./re-review-prompt.md)" -> "All findings addressed?";
    "All findings addressed?" -> "Append completion to ledger, mark todo complete" [label="yes"];
    "All findings addressed?" -> "R = 5?" [label="no"];
    "R = 5?" -> "Fix round R of 5: R≤3 resume implementer; R≥4 fresh implementer, more capable model" [label="no - next round"];
    "R = 5?" -> "Adjudicate each open finding" [label="yes - breaker trips"];
    "Adjudicate each open finding" -> "Any load-bearing finding?";
    "Any load-bearing finding?" -> "STOP: report BLOCKED to human partner" [label="yes"];
    "Any load-bearing finding?" -> "Park findings in ledger with rulings" [label="no"];
    "Park findings in ledger with rulings" -> "Append completion to ledger, mark todo complete";
    "Append completion to ledger, mark todo complete" -> "More tasks remain?";
    "More tasks remain?" -> "Dispatch implementer subagent (./implementer-prompt.md)" [label="yes"];
    "More tasks remain?" -> "Dispatch final code reviewer (../requesting-code-review/code-reviewer.md)" [label="no"];
    "Dispatch final code reviewer (../requesting-code-review/code-reviewer.md)" -> "Final findings? ONE fix dispatch, one scoped re-review, adjudicate residuals";
    "Final findings? ONE fix dispatch, one scoped re-review, adjudicate residuals" -> "Final review clean: delete this plan's workspace";
    "Final review clean: delete this plan's workspace" -> "Use superpowers-brain:finishing-a-development-branch";
}

Setup

Ensure the work happens in an isolated workspace: use superpowers-brain:using-git-worktrees to create one or verify the existing one. Never start implementation on a main/master branch without your human partner's explicit consent.

Conversation memory does not survive compaction. In real sessions, controllers that lost their place have re-dispatched entire completed task sequences — the single most expensive failure observed. Track progress in a ledger file, not only in todos.

File paths resolve against this skill's own directory. There is no plugin root in this import: every scripts/… reference below means /subagent-driven-development/scripts/… — the concrete path of the skill directory you loaded this file from. Resolve it once at setup and reuse the absolute path. The same applies to sibling-skill references such as ../requesting-code-review/code-reviewer.md, which resolve relative to this skill directory.

• Each plan owns a workspace: at skill start, run this skill's

scripts/sdd-workspace PLAN_FILE — it prints the plan's git-ignored directory (/.superpowers/sdd//), home to every artifact for THIS plan: ledger, briefs, reports, review packages. Another plan's directory is never yours to read or write.

• Check for this plan's ledger at /progress.md. If its first

line names your plan file, tasks with a Task : complete line are DONE — do not re-dispatch them; resume at the first task without one. A task whose last line is a fix round is mid-loop: resume the loop at the next round. A ledger whose first line names a different plan file — or a stray ledger at the old flat path .superpowers/sdd/progress.md — is another plan's progress: leave it in place and start your own, fresh.

• Create the ledger with its identity as the first line:

# SDD ledger — plan: .

• The ledger is your recovery map: the commits it names exist in git even

when your context no longer remembers creating them. After compaction, trust the ledger and git log over your own recollection.

• git clean -fdx will destroy the workspace (it's git-ignored scratch); if

that happens, recover from git log.

> Brain mode: In a Brain vault (a .brain/ directory exists in this > directory or an ancestor), PLAN_FILE is the vault artefact > (_Temporal/Plans/yyyy-mm/yyyymmdd-plan~{Title}.md). The workspace still > belongs to the code repo — sdd-workspace resolves it from > git rev-parse --show-toplevel, and it never lands in the vault. > > Brain plan basenames contain spaces and a ~, so the workspace directory > does too (.superpowers/sdd/20260504-plan~Feature plan/). Quote every plan, > workspace, brief, report, and review-package path — in script invocations, > in rm -rf "", and in the paths you paste into dispatch prompts > ("/task-3-brief.md"). An unquoted path is how a subagent reads > the wrong file and how rm -rf deletes the wrong thing. > > Once the workspace is resolved, mark the plan as implementing: > brain_edit(resource="artefact", path="", operation="edit", frontmatter={"status": "implementing"}) > (omit body — frontmatter-only change). Whichever executor runs owns these > transitions; superpowers-brain:executing-plans states the same contract.

Read the plan once, note its context and Global Constraints, and create a todo per task.

Before dispatching Task 1, scan the plan once for conflicts:

• tasks that contradict each other or the plan's Global Constraints
• anything the plan explicitly mandates that the review rubric treats as a

defect (a test that asserts nothing, verbatim duplication of a logic block)

Present everything you find to your human partner as one batched question — each finding beside the plan text that mandates it, asking which governs — before execution begins, not one interrupt per discovery mid-plan. If the scan is clean, proceed without comment. The review loop remains the net for conflicts that only emerge from implementation.

Model Selection

Use the least powerful model that can handle each role to conserve cost and increase speed.

Mechanical implementation tasks (isolated functions, clear specs, 1-2 files): use a fast, cheap model. Most implementation tasks are mechanical when the plan is well-specified.

Integration and judgment tasks (multi-file coordination, pattern matching, debugging): use a standard model.

Architecture and design tasks: use the most capable available model. The final whole-branch review is one of these — dispatch it on the most capable available model, not the session default.

Review tasks: choose the model with the same judgment, scaled to the diff's size, complexity, and risk. A small mechanical diff does not need the most capable model; a subtle concurrency change does. Scoped re-reviews of small fix diffs take a cheap-to-mid tier.

Fix-loop escalation (rounds 4-5): use a model at least one tier above the implementer that got stuck.

Always specify the model explicitly when dispatching a subagent. An omitted model inherits your session's model — often the most capable and most expensive — which silently defeats this section.

Turn count beats token price. Wall-clock and context cost scale with how many turns a subagent takes, and the cheapest models routinely take 2-3× the turns on multi-step work — costing more overall. Use a mid-tier model as the floor for reviewers and for implementers working from prose descriptions. When the task's plan text contains the complete code to write, the implementation is transcription plus testing: use the cheapest tier for that implementer. Single-file mechanical fixes also take the cheapest tier.

Task complexity signals (implementation tasks):

• Touches 1-2 files with a complete spec → cheap model
• Touches multiple files with integration concerns → standard model
• Requires design judgment or broad codebase understanding → most capable model

The Task Loop

Everything you paste into a dispatch prompt — and everything a subagent prints back — stays resident in your context for the rest of the session and is re-read on every later turn. Hand artifacts over as files.

1. Dispatch the implementer

Record BASE (git rev-parse HEAD) before dispatching — the review package and fix-round diffs need it.

• Task brief: before dispatching an implementer, run this skill's

scripts/task-brief PLAN_FILE N — it extracts the task's full text to a uniquely named file and prints the path. Compose the dispatch so the brief stays the single source of requirements. Your dispatch should contain: (1) one line on where this task fits in the project; (2) the brief path, introduced as "read this first — it is your requirements, with the exact values to use verbatim"; (3) interfaces and decisions from earlier tasks that the brief cannot know; (4) your resolution of any ambiguity you noticed in the brief; (5) the report-file path and report contract. Exact values (numbers, magic strings, signatures, test cases) appear only in the brief. Never make a subagent read the whole plan file.

• Report file: name the implementer's report file after the brief

(brief …/task-N-brief.md → report …/task-N-report.md) and put it in the dispatch prompt. The implementer writes the full report there and returns only status, commits, a one-line test summary, and concerns.

• A dispatch prompt describes one task, not the session's history. Do not

paste accumulated prior-task summaries ("state after Tasks 1-3") into later dispatches — a real session's dispatch hit 42k chars of which 99% was pasted history. A fresh subagent needs its task, the interfaces it touches, and the global constraints. Nothing else.

• If an earlier task parked a finding in the area this task touches, carry

a pointer to that ledger entry in the dispatch.

• Record the implementer's agent identity from the dispatch result —

fix-loop rounds 1-3 resume this agent.

• Never dispatch multiple implementation subagents in parallel (conflicts).

Template: [implementer-prompt.md](implementer-prompt.md)

2. Handle the report

Implementer subagents report one of four statuses. Handle each appropriately:

DONE: Generate the review package (scripts/review-package PLAN_FILE BASE HEAD, from this skill's directory — it prints the unique file path it wrote; BASE is the commit you recorded before dispatching the implementer — never HEAD~1, which silently drops all but the last commit of a multi-commit task), then dispatch the task reviewer with the printed path.

DONEWITHCONCERNS: The implementer completed the work but flagged doubts. Read the concerns before proceeding. If the concerns are about correctness or scope, address them before review. If they're observations (e.g., "this file is getting large"), note them and proceed to review.

NEEDS_CONTEXT: The implementer needs information that wasn't provided. Provide the missing context and re-dispatch.

**BLOCKED

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Rob-Morris
• Source: Rob-Morris/agent-skills
• License: MIT

Install and usage instructions live in the source repository linked above.