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 Owl-Listener/designpowers --skill design-reviewgit clone --depth 1 https://github.com/Owl-Listener/designpowersWrote 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/owl-listener/designpowers/design-review)<a href="https://agentmods.dev/skills/owl-listener/designpowers/design-review"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/design-review/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/owl-listener/designpowers/design-review"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/design-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00103 | $0.01587 |
| Opus 5 | $0.00051 | $0.00794 |
| Sonnet 5 | $0.00021 | $0.00317 |
| Haiku 4.5 | $0.00010 | $0.00159 |
Grade A, and why
design-review 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 10d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Review (the review lane)
Most design work is improving something that already exists, not starting from a blank page. This is the review-only lane: it takes an existing artefact — a screenshot, a live URL, a prototype, or existing code/markup — and runs it through the same reviewers and reconciliation the full pipeline uses, but without discovery, strategy, design, or build.
It's the counterpart to the build lane. The build lane asks "what are we designing?" and creates. The review lane asks "what are we evaluating?" and critiques.
When to Use
Route here, instead of the build pipeline, when the user already has something:
- "Review / audit / critique this [screen / page / app / flow / component]"
- "What's wrong with this?" / "How can I improve this?" / "Is this accessible?"
- They share a screenshot, a URL, or point at existing code/markup
- They want a usability, accessibility, or craft assessment of work that already exists
If the user wants to build something new, use the normal pipeline (design-discovery → …). If it's genuinely unclear which they want, ask one question: "Do you want me to review something you already have, or design something new?"
What this lane skips and why
It deliberately skips discovery, research, strategy, inspiration, planning, and build — there is nothing to build. It does not skip accessibility, usability, or craft evaluation. The point is a rigorous, reconciled critique, fast, then a decision about what to fix.
Process
Step 1: Get the artefact
Establish what you're reviewing and take it in directly — always evaluate the actual artefact, never a description of it:
| Artefact | How to take it in |
|---|---|
| Screenshot / image | Read the image directly |
| Live URL | Load and screenshot it (browser tooling); note interactive states |
| Existing code / markup | Read the relevant files; if it runs, screenshot the running build |
A DESIGN.md + a build |
Read the spec via design-md, then review the build against it |
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.
- 10d ago First seen · 124 lines · 103 tokens per session scan A e4e394a19002
design-review is a skill published in the GitHub repository Owl-Listener/designpowers (245 stars, last pushed 2mo ago), licensed MIT. It adds 103 tokens to every session and 1,587 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
doubt-driven-review
In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.
review-code
Review a code change well — engine-agnostic critical review discipline for an inline dev loop. Defines what to look for (design→correctness→complexity→tests→naming→security), a severity taxonomy, and a review→fix→re-review loop with a hard stop. Use on "review this code", "review my diff", "is this change good"…
code-review
AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security). Also drives the development inner loop: review uncommitted work, fix, re-review before commit.
accessibility-a11y
Semantic HTML, keyboard navigation, focus states, ARIA labels, skip links, and WCAG contrast requirements. Use when ensuring accessibility compliance, implementing keyboard navigation, or adding screen reader support.
code-quality
Drive static-analysis code quality in pi-agent-dashboard with Biome (analyze → fix → test), in changed-files or whole-repo mode. Use when asked to "improve code quality", "lint and fix", "clean up warnings", "fix Biome issues", "run static analysis", or when setting a code-quality goal. Skip for one-line edits.