Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/naimkatiman/continuous-improvementnpx agentmods add commands/naimkatiman/continuous-improvement/superpowersWrote 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/commands/naimkatiman/continuous-improvement/superpowers)<a href="https://agentmods.dev/commands/naimkatiman/continuous-improvement/superpowers"><img src="https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/superpowers/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/commands/naimkatiman/continuous-improvement/superpowers"><img src="https://agentmods.dev/badge/commands/naimkatiman/continuous-improvement/superpowers.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 | $0.00055 | $0.02962 |
| Opus 5.5 | $0.00022 | $0.01185 |
| Sonnet 5.5 | $0.00011 | $0.00592 |
| Haiku 4.5 | $0.00006 | $0.00296 |
Grade A, and why
superpowers 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 1mo 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/superpowers
/superpowers is the dispatcher, not a peer skill. It does not do work itself; it routes each user task to the correct Law-aligned specialist so the right discipline fires automatically instead of the agent skipping a step.
The 7 Laws define what discipline must be applied. /superpowers decides which specialist enforces it for this specific task, across four sources installed from this marketplace.
Routing surface (four sources)
| Source | Where it lives | Examples of what it routes to |
|---|---|---|
continuous-improvement (this plugin) |
bundled — always present | gateguard (Law 1), tdd-workflow (Law 3+4), verification-loop (Law 4), wild-risa-balance (Law 2), proceed-with-the-recommendation (all 7), ralph (Law 6), workspace-surface-audit (Law 1) |
obra/superpowers (Jesse Vincent) |
vendored at third-party/superpowers/, pinned SHA f2cbfbe (v5.1.0) |
superpowers:brainstorming, :writing-plans, :executing-plans, :test-driven-development, :systematic-debugging, :requesting-code-review, :receiving-code-review, :verification-before-completion, :dispatching-parallel-agents, :using-git-worktrees, :finishing-a-development-branch, :subagent-driven-development, :writing-skills, :using-superpowers |
addyosmani/agent-skills |
vendored at third-party/addy-agent-skills/, pinned SHA 742dca5 (v1.0.0) |
spec-driven-development, source-driven-development, context-engineering, idea-refine, incremental-implementation, code-review-and-quality, code-simplification, security-and-hardening, debugging-and-error-recovery, performance-optimization, api-and-interface-design, frontend-ui-engineering, browser-testing-with-devtools, ci-cd-and-automation, deprecation-and-migration, documentation-and-adrs, git-workflow-and-versioning, planning-and-task-breakdown, shipping-and-launch |
ruflo-swarm (ruvnet) |
vendored at third-party/ruflo-swarm/, pinned SHA addb5cd (v0.2.0) |
swarm-init, monitor-stream; swarm_* and agent_* MCP tools; /swarm, /watch |
oh-my-claudecode (Yeachan-Heo) |
vendored at third-party/oh-my-claudecode/, pinned SHA 4820f56 (v5.3.0) |
37 skills + 19 agents — release, ultragoal, launch, team, trace, visual-verdict, debug, review, research, deep-interview, autopilot, autoresearch, plus a separate ralph (overlaps with our /ralph — see "Distinct variants" below) |
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.
- 1mo ago Changed 023c03b93ee9
- 1mo ago Changed 1e415c32725a
- 1mo ago First seen · 181 lines · 55 tokens per session scan A 12485c1b213c
superpowers is a command published in the GitHub repository naimkatiman/continuous-improvement (9 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 2,962 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
ap-swarm
Run a MultiAgentRuntime swarm in file mode — local journal at .runtime/conversation.md, no network.
reflect-promote
Promote learnings from skills to global CLAUDE.md.
reflect-meta
Show meta-learning statistics and pattern performance.
reflect-stats
Show cross-skill learning statistics.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.