subagent-driven-development
Use when executing implementation plans with independent tasks in the current session
Install / Use
npx skills add obra/superpowers --skill subagent-driven-developmentInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
LegalSupported Platforms
Our assessment of subagent-driven-development
subagent-driven-development scores 95/100 on our quality scale, 8th of 55 Legal skills we index (top 15%).
Its SKILL.md is 32 KB long, well organised into 15 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 290,965 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so subagent-driven-development is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
subagent-driven-development compared with similar skills
All 4 of these similar skills score higher than subagent-driven-development; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| subagent-driven-development (this skill)by obra | 95 | 291.0k | 3d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
Frequently asked questions
- How do I install subagent-driven-development?
- Run
npx skills add obra/superpowers --skill subagent-driven-development. The install tabs above show the steps for each supported agent. - Which AI agents does subagent-driven-development work with?
- It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is subagent-driven-development safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is subagent-driven-development still maintained?
- The repository was last updated 3 days ago, so subagent-driven-development is actively maintained.
Skill content
View source on GitHubname: subagent-driven-development description: Use when executing implementation plans with independent tasks in the current session
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 the four named below, or all tasks complete. "Should I continue?" prompts and progress summaries waste their time — they asked you to execute the plan, so execute it.
Rulings, not stalls. A running plan does not wait on a human. Conflicts,
ambiguities, plan defects, a cap you would have asked to exceed — decide
them. The spec is the binding authority, the plan is its argument, and your
judgment settles what neither answers. Record every decision in the ledger as
Ruling: <what you decided> — <why> — <what it costs if wrong>, and keep
going. A wrong ruling costs rework your human partner can see and undo; a
session parked on a question costs their whole day and buys nothing.
Four things stop you, and only these: an irreversible or destructive operation; a security-sensitive action; a side effect outside this worktree that norms say you ask about first (a merge, a push to a shared branch, a publish); and a plan so broken that every path forward is a guess. For those, stop and ask.
When to Use
digraph when_to_use {
"Have implementation plan?" [shape=diamond];
"Tasks mostly independent?" [shape=diamond];
"Partner chose inline, or no subagent tool?" [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?" -> "Partner chose inline, or no subagent tool?" [label="yes"];
"Tasks mostly independent?" -> "Manual execution or brainstorm first" [label="no - tightly coupled"];
"Partner chose inline, or no subagent tool?" -> "executing-plans" [label="yes"];
"Partner chose inline, or no subagent tool?" -> "subagent-driven-development" [label="no"];
}
vs. Executing Plans (inline):
- Fresh subagent per task (no context pollution) instead of one context doing every task
- Review after each task (spec compliance + code quality) instead of only at the end
- Costs a fresh context per task and per review; inline costs one context plus one final reviewer
- Both run in this session, share the same plan workspace and ledger, and never pause 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];
"Rule on the conflict, ledger the ruling" [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];
"Rule and continue; stop only if every path forward is a guess" [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: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?" -> "Rule on the conflict, ledger the ruling" [label="yes"];
"Rule on the conflict, ledger the ruling" -> "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?" -> "Rule and continue; stop only if every path forward is a guess" [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:finishing-a-development-branch";
}
Setup
Ensure the work happens in an isolated workspace: use superpowers: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.
- Each plan owns a workspace: at skill start, run this skill's
bash scripts/sdd-workspace PLAN_FILE— it prints the plan's git-ignored directory (under<repo-root>/.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
<workspace>/progress.md. If its first line names your plan file, tasks with aTask <N>: completeline 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: <plan file path>. - 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 logover your own recollection. git clean -fdxwill destroy the workspace (it's git-ignored scratch); if that happens, recover fromgit log.
Read the plan once, note its context and Global Constraints, and create a todo per task. If the plan names a Spec, read that too: the spec is the authority the plan argues from, and conflicts inside the plan resolve against it. A plan with no reachable spec gets a ledger note saying so — rulings made without one are provisional.
Before dispatching Task 1, scan the plan once for conflicts, writing down what you checked as you check it:
- 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)
The scan's output is a table, not a verdict. One row for every pair of tasks that share a file or an interface: the two tasks, what one produces against what the other consumes, and what you found. One row for every task: whether its own text agrees with itself — the tests it specifies against the code it specifies, the files it creates against the files it later touches. "The scan is clean" without those rows is not a scan you ran.
Write the table to the ledger. Rule on everything you find before execution begins — each finding against the plan text that mandates it — and record each ruling in the ledger. If the scan is clean, proceed without comment. Rule on each conflict it surfaces — the spec is the binding authority, the plan is its argument — record the ruling beside its row, and dispatch Task 1. 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-
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
