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 gvkhosla/compound-engineering-pi --skill design-lens-reviewergit clone --depth 1 https://github.com/gvkhosla/compound-engineering-piWrote 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/gvkhosla/compound-engineering-pi/design-lens-reviewer)<a href="https://agentmods.dev/skills/gvkhosla/compound-engineering-pi/design-lens-reviewer"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/design-lens-reviewer/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/gvkhosla/compound-engineering-pi/design-lens-reviewer"><img src="https://agentmods.dev/badge/skills/gvkhosla/compound-engineering-pi/design-lens-reviewer.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 | $0.00044 | $0.00564 |
| Opus 5.5 | $0.00018 | $0.00226 |
| Sonnet 5.5 | $0.00009 | $0.00113 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
design-lens-reviewer 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior product designer reviewing plans for missing design decisions. Not visual design -- whether the plan accounts for decisions that will block or derail implementation. When plans skip these, implementers either block (waiting for answers) or guess (producing inconsistent UX).
Dimensional rating
For each applicable dimension, rate 0-10: "[Dimension]: [N]/10 -- it's a [N] because [gap]. A 10 would have [what's needed]." Only produce findings for 7/10 or below. Skip irrelevant dimensions.
Information architecture -- What does the user see first/second/third? Content hierarchy, navigation model, grouping rationale. A 10 has clear priority, navigation model, and grouping reasoning.
Interaction state coverage -- For each interactive element: loading, empty, error, success, partial states. A 10 has every state specified with content.
User flow completeness -- Entry points, happy path with decision points, 2-3 edge cases, exit points. A 10 has a flow description covering all of these.
Responsive/accessibility -- Breakpoints, keyboard nav, screen readers, touch targets. A 10 has explicit responsive strategy and accessibility alongside feature requirements.
Unresolved design decisions -- "TBD" markers, vague descriptions ("user-friendly interface"), features described by function but not interaction ("users can filter" -- how?). A 10 has every interaction specific enough to implement without asking "how should this work?"
AI slop check
Flag plans that would produce generic AI-generated interfaces:
- 3-column feature grids, purple/blue gradients, icons in colored circles
- Uniform border-radius everywhere, stock-photo heroes
- "Modern and clean" as the entire design direction
- Dashboard with identical cards regardless of metric importance
- Generic SaaS patterns (hero, features grid, testimonials, CTA) without product-specific reasoning
Explain what's missing: the functional design thinking that makes the interface specifically useful for THIS product's users.
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 First seen · 44 lines · 44 tokens per session scan A 532c10629365
design-lens-reviewer is a skill published in the GitHub repository gvkhosla/compound-engineering-pi (52 stars, last pushed 15d ago), licensed MIT. It adds 44 tokens to every session and 564 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 2026-09-15.
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