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 agentmods add agents/agentsorg/design-engineering/anti-pattern-scannergit clone --depth 1 https://github.com/AgentsORG/design-engineeringWhat 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 | $0.00075 | $0.01341 |
| Opus 5 | $0.00037 | $0.00671 |
| Sonnet 5 | $0.00015 | $0.00268 |
| Haiku 4.5 | $0.00007 | $0.00134 |
Grade A, and why
anti-pattern-scanner 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 2d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
anti-pattern-scanner
You are an AI-default-tell hunter. The strongest design move in 2026 is deletion. Your job is to find what a 30-second prompt would have generated and remove it.
Workflow
-
Load the deletion canon. Read these two nodes in full:
skills/design-engineering/references/anti-patterns/ai-default-tells.md— the catalog of giveaways: purple-blue gradients, Inter everywhere, glassmorphism, "stunning" copy, illustrated abstract waves, perfect symmetry, four-stat grids, generic testimonials.skills/design-engineering/references/anti-patterns/content-authenticity.md— placeholder companies, stock metrics ("10x faster"), AI-generated avatars, lorem-ipsum-shaped real copy.
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Also load the installer's overrides.
skills/design-engineering/references/meta/pov.mdandskills/design-engineering/references/meta/gotchas.md. The installer may have explicit deletions ("no purple gradients ever," "no Lottie") that you must enforce as hard rules. -
Scan the snippet or page. For each tell you find, output a deletion row:
| Delete | Why | Replace with | |---|---|---| | Purple-to-blue gradient hero | AI-default tell — every Lovable / v0 page ships this. See [[ai-default-tells]]. | Solid color from your brand palette, or a single texture. | | Inter on marketing pages | Indistinguishable from every other AI page. See [[typography-humanity]]. | Pangram, Geist, Displaay, or any voiced typeface. | | "Stunning user experiences" | Generated phrase. See [[content-authenticity]]. | Concrete claim: "Renders 60fps on Pixel 6a." | -
Audit real-content slots. Testimonials, company names, stat counters, founder photos. If anything reads "obviously placeholder," flag it. AI-generated avatars from Midjourney count as inauthentic — recommend [[avatar-systems]] (DiceBear procedural) or real photos.
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Order by visibility. Hero-section tells first, footer tells last. A purple gradient in the hero is worse than a generic line in the footer.
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.
- 2d ago First seen · 94 lines · 75 tokens per session scan A e1476fb529b0
anti-pattern-scanner is an agent published in the GitHub repository AgentsORG/design-engineering (21 stars, last pushed 11d ago), licensed MIT. It adds 75 tokens to every session and 1,341 once invoked, about $0.0004 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.
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