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 verification-before-shippinggit 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/verification-before-shipping)<a href="https://agentmods.dev/skills/owl-listener/designpowers/verification-before-shipping"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/verification-before-shipping/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/verification-before-shipping"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/verification-before-shipping.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 | $0.00035 | $0.00963 |
| Opus 5 | $0.00017 | $0.00481 |
| Sonnet 5 | $0.00007 | $0.00193 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
verification-before-shipping 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 9d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verification Before Shipping
Do not say it is done until you have proof. This skill prevents the most common failure mode in design work — declaring completion based on intent rather than evidence.
The Rule
NEVER claim work is complete, fixed, passing, or ready without running verification and confirming the output. "I believe this works" is not verification. "I ran these checks and here are the results" is.
When to Use
- Before declaring a design task complete
- Before moving from one phase to the next
- Before handoff to engineering
- Before creating a PR or committing design artefacts
- Any time you are about to say "done"
Process
Step 1: Check Against the Plan
If a design plan exists:
- Every task in the plan is marked complete
- Every verification criterion in the plan has been met
- No tasks were skipped or deferred without explicit user approval
Step 2: Check Against the Brief
Reference the design brief:
- The stated problem is addressed
- All identified personas are served
- Success criteria are met or measurable
- Nothing in "out of scope" crept into scope (and vice versa)
Step 3: Accessibility Verification
Run — do not guess:
If code exists:
- Automated accessibility scan (axe-core, Lighthouse, or equivalent) — report results
- Keyboard navigation test — report results
- Screen reader test (at minimum, check heading structure and form labels)
- Zoom to 200% — report results
- Check prefers-reduced-motion behaviour — report results
If design artefacts only:
- Contrast ratios verified with a tool (not by eye)
- Touch targets measured (not estimated)
- Heading hierarchy documented
- All states designed (not just the happy path)
Step 4: Content Verification
- All placeholder text has been replaced with real content
- Error messages are written (not "TODO")
- Alt text is present for all images
- Labels are specific and descriptive
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.
- 9d ago First seen · 126 lines · 35 tokens per session scan A 8c8df52cdf6c
verification-before-shipping is a skill published in the GitHub repository Owl-Listener/designpowers (243 stars, last pushed 2mo ago), licensed MIT. It adds 35 tokens to every session and 963 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 2026-08-30.
Other skills, from other repositories
scenario-design
Draft real-life test SCENARIOS (not smoke tests) from a change/feature spec. Derives edge-case, performance, frontend-quirk and error-handling scenarios with ISTQB techniques, routes each to a test level, and writes test-plan.md, emitting clarification questions on a spec gap. Use on "design test scenarios", "what…
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.
tailwind-shadcn
Tailwind CSS utility patterns with shadcn/ui component usage, theming via CSS variables, and responsive design. Use when styling components, installing shadcn components, implementing dark mode, or creating consistent design systems.
anti-slop-frontend
A mechanical, countable anti-slop checklist for AI-generated frontend. Catches the specific signatures an undirected model defaults to: AI-purple glows, Inter-everywhere, em-dashes, div-based fake screenshots, eyebrow-on-every-section, beige+brass "premium" palettes, generic Jane Doe / Acme data. Advisory layer that…
frontend-mockup-loop
Plan, build, and iterate UX-friendly frontend mockups via a ground→contract→mockup→test→fix→learn loop, acting as an expert UX designer who grounds every decision in externally documented public design rules (Nielsen heuristics, Laws of UX, WCAG, GOV.UK/USWDS/Material). Uses the bundled servemockup, scoremockup, and…
frontend-mockup-loop-dashboard
Dashboard-specific adapter on the generic frontend-mockup-loop skill: binds the 7-step design loop to pi-agent-dashboard component sources, theme-system tokens, and isolated verification. Use when designing/redesigning any pi-agent-dashboard client surface. Triggers: "design a dashboard screen", "mockup a dashboard…