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.
npx skills add regen-coordination/org-os-template --skill superpowers-subagent-driven-developmentgit clone --depth 1 https://github.com/regen-coordination/org-os-templateWrote 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.
[](https://agentmods.dev/skills/regen-coordination/org-os-template/superpowers-subagent-driven-development)<a href="https://agentmods.dev/skills/regen-coordination/org-os-template/superpowers-subagent-driven-development"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/superpowers-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.
<a href="https://agentmods.dev/skills/regen-coordination/org-os-template/superpowers-subagent-driven-development"><img src="https://agentmods.dev/badge/skills/regen-coordination/org-os-template/superpowers-subagent-driven-development.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00921 |
| Opus 5 | $0.00017 | $0.00461 |
| Sonnet 5 | $0.00007 | $0.00184 |
| Haiku 4.5 | $0.00003 | $0.00092 |
Grade A, and why
superpowers-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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with two-stage review after each: spec compliance review first, then code quality review.
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 + two-stage review (spec then quality) = high quality, fast iteration
When to Use
Use when:
- You have an implementation plan with independent tasks
- You want to stay in the current session (no context switch)
- Tasks are mostly independent (not tightly coupled)
vs. Executing Plans: Same session, fresh subagent per task, two-stage review, faster iteration.
vs. Manual execution: Subagents follow TDD naturally, fresh context per task, parallel-safe.
The Process
- Read plan — extract all tasks with full text, note context, create TodoWrite
- Per task:
- Dispatch implementer subagent with full task text + context
- Answer any questions from implementer
- Implementer implements, tests, commits, self-reviews
- Dispatch spec reviewer subagent — confirm code matches spec
- If issues: implementer fixes, re-review
- Dispatch code quality reviewer subagent — review implementation quality
- If issues: implementer fixes, re-review
- Mark task complete
- After all tasks:
- Dispatch final code reviewer for entire implementation
- Use
superpowers:finishing-a-development-branchto complete
Model Selection
Use the least powerful model that can handle each role:
- Mechanical tasks (1-2 files, clear specs): fast/cheap model
- Integration/judgment (multi-file, pattern matching): standard model
- Architecture/design/review: most capable model
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.
- 8d ago First seen · 103 lines · 34 tokens per session scan A 01783c255565
superpowers-subagent-driven-development is a skill published in the GitHub repository regen-coordination/org-os-template (5 stars, last pushed 6d ago), licensed MIT. It adds 34 tokens to every session and 921 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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openspec-verify-change
Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.
openspec-update-change
Update an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Never edits code.
openspec-new-change
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.