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 skills/douglance/sdlc-plugin/visual-designnpx skills add douglance/sdlc-plugin --skill visual-designgit clone --depth 1 https://github.com/douglance/sdlc-pluginWhat 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 | $0.00029 | $0.00579 |
| Opus 5 | $0.00015 | $0.00290 |
| Sonnet 5 | $0.00006 | $0.00116 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
visual-design 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use lifecycle-documentation only when the result needs a durable artifact or handoff.
Design and verify the user-facing surface. Work from the user's task, design the whole composition and every state, meet accessibility, then LOOK — render it, screenshot it, and judge the real result.
What to cover
- User-centered — start from the user, the job, and the success state, not the data model.
- Composition & hierarchy — balance, spacing, alignment, visual hierarchy, typographic scale. No dead zones, squashing, overflow, clipping, or floating orphans.
- Specificity — proven structures may scaffold the work, but hierarchy, typography, palette, assets, density, interaction, and copy must respond to this product and brief. If another product could use the result after swapping only its logo and nouns, revise it.
- Generated-design defaults — reject unprompted purple/blue gradients, decorative grid backgrounds, bento-box sectioning, oversized hero type replacing meaningful imagery, arbitrary offset composition, repeated stock assets, and gratuitous confetti/particles. These remain valid when the brief or product context earns them.
- Data visualization — use realistic data, truthful encodings, labeled units/scales, legible legends/tooltips, and responsive layouts. Decorative pseudo-data does not count as a chart.
- States — empty, loading, error, populated, and responsive breakpoints.
- Accessibility — contrast, focus order, keyboard operability, labels/alt text, reduced-motion.
Visual verification (non-negotiable)
LOOK before declaring done. A passing behavioral test and a clean console do not verify visual composition. Inspect a rendered capture, judge the whole composition, and use that capture as evidence for visual claims. Iterate until the result is coherent and specific to the brief.
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 · 44 lines · 29 tokens per session scan A 2d5132455a3c
visual-design is a skill published in the GitHub repository douglance/sdlc-plugin (4 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 579 once invoked, about $0.0001 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 2026-08-31.
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