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 RudyCity/superagent --skill antislop-humangit clone --depth 1 https://github.com/RudyCity/superagentWrote 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/rudycity/superagent/antislop-human)<a href="https://agentmods.dev/skills/rudycity/superagent/antislop-human"><img src="https://agentmods.dev/badge/skills/rudycity/superagent/antislop-human/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/rudycity/superagent/antislop-human"><img src="https://agentmods.dev/badge/skills/rudycity/superagent/antislop-human.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 | $0.00031 | $0.02736 |
| Opus 5.5 | $0.00012 | $0.01094 |
| Sonnet 5.5 | $0.00006 | $0.00547 |
| Haiku 4.5 | $0.00003 | $0.00274 |
Grade A, and why
antislop-human 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.
This is a copy
100% identical to antislop-human — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
antislop-human
Anti Slop: Rules for AI Coding Agents. Human skill
Part of the antislop system. Read together with
antislop.md(the core). This skill deep-dives the human concern: the UI must stay usable by people with different eyes, hands, and setups. Contrast, keyboard, focus, states, and the mobile details that exclude people.
How to use this skill
- Load together with
antislop.mdwhenever the task builds or edits UI. The core holds the mechanism (the purpose test, the three tiers, the Delivery Gate); this skill holds the human-side depth: the parts of a UI that exclude people with different eyes, hands, and setups. - Every entry has the same shape: Tell (the pattern), Why (who it excludes, and why it reads as unfinished), Fix (what to do instead), with the governing core rule cited as R-XX.
- Accessibility is not a checklist of extras bolted on at the end. It is part of the core promise that "the UI holds up" (C-4). The Delivery Gate in the core remains the gate; the "Human Skill Checklist" at the end of this file is the supplement to run alongside it.
- The contrast checker (formula + reference table + script) lives in this skill. Use it for every color pairing you cannot verify by eye.
- This skill keeps only the mobile details that exclude people: zooming, and the on-screen keyboard.
Color & Contrast
Low-Contrast Text
- Tell: light grey text on a white or near-white background, thin body text, muted labels chosen because they look "elegant" but are hard to read.
- Why: it excludes low-vision users and everyone in bright light. It is a visual choice made without checking the standard, which is exactly the kind of default the filter exists to catch.
- Fix: meet WCAG AA minimums (R-25): 4.5:1 for normal text, 3:1 for large text (18px+). Compute the ratio; do not eyeball it.
Text Over a Photo or Gradient
- Tell: white text placed directly over an image or gradient that is light in some areas, checked at one bright spot only.
- Why: contrast is local. Where the image is light, the text drops below 4.5:1 even if the hero still "looks" fine. R-25 requires testing the whole area the text passes over, not a single point.
- Fix: add a scrim or a solid color block behind the text, then verify the worst spot, not the best. If any part of the text area fails, the treatment fails.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 148 lines · 31 tokens per session scan A 5bc7c8e56cc7
antislop-human is a skill published in the GitHub repository RudyCity/superagent (51 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 2,736 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to antislop-human, differing in 5 lines, and is treated as a copy.
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