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 tdimino/claude-code-minoan --skill stop-slopgit clone --depth 1 https://github.com/tdimino/claude-code-minoanWrote 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/tdimino/claude-code-minoan/stop-slop)<a href="https://agentmods.dev/skills/tdimino/claude-code-minoan/stop-slop"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/stop-slop/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/tdimino/claude-code-minoan/stop-slop"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/stop-slop.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 | $0.00059 | $0.00927 |
| Opus 5 | $0.00030 | $0.00464 |
| Sonnet 5 | $0.00012 | $0.00185 |
| Haiku 4.5 | $0.00006 | $0.00093 |
Grade A, and why
stop-slop 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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stop Slop
Eliminate predictable AI writing patterns. Produce clear, specific, human-sounding prose across any register.
Step 1: Detect register
Infer the register from context before applying rules. Different registers tolerate different patterns.
| Signal | Register |
|---|---|
| Citations, methodology, "we hypothesize" | academic |
| API docs, READMEs, changelogs, error messages | technical |
| Fiction, essays, memoir, creative nonfiction | narrative |
| Blog posts, social media, emails | casual |
| Reports, proposals, business comms | professional |
If the user specifies a register, use it. See references/registers.md for per-register acceptable vs. flagged patterns.
Step 2: Remove slop
Apply these rules, adjusted for register:
-
Cut filler phrases and AI vocabulary. Remove throat-clearing openers, chatbot artifacts, significance inflation, and words that appear 100-1,000x more in LLM output than human text. See references/phrases.md.
-
Break formulaic structures. Avoid binary contrasts, dramatic fragmentation, format slop, synonym cycling, rule-of-three overuse, and generic conclusions. See references/structures.md.
-
Use simple constructions. Prefer "is" over "serves as." Prefer "has" over "boasts." Prefer "use" over "leverage." Active voice. Positive form.
-
Be specific. Replace vague claims with dates, names, numbers, sources. "Significant improvement" becomes "latency dropped from 340ms to 90ms."
-
Vary rhythm. Mix sentence lengths. Two items in a list beat three. End paragraphs differently from each other.
-
Trust readers. State facts. Skip softening, justification, hand-holding. If a metaphor needs explaining, rewrite the metaphor.
-
Have a voice. React to facts, don't just report them. Acknowledge complexity. Let personality through.
See references/positive.md for what good writing does (not just what to avoid).
What ships with it
8 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.
- 10d ago First seen · 90 lines · 59 tokens per session scan A 171e2d376638
stop-slop is a skill published in the GitHub repository tdimino/claude-code-minoan (41 stars, last pushed 2d ago), licensed MIT. It adds 59 tokens to every session and 927 once invoked, about $0.0003 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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