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 painhardcore/pstack --skill unslopgit clone --depth 1 https://github.com/painhardcore/pstackWrote 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/painhardcore/pstack/unslop)<a href="https://agentmods.dev/skills/painhardcore/pstack/unslop"><img src="https://agentmods.dev/badge/skills/painhardcore/pstack/unslop/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/painhardcore/pstack/unslop"><img src="https://agentmods.dev/badge/skills/painhardcore/pstack/unslop.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 | $0.00014 | $0.01620 |
| Opus 5.5 | $0.00006 | $0.00648 |
| Sonnet 5.5 | $0.00003 | $0.00324 |
| Haiku 4.5 | $0.00001 | $0.00162 |
Grade A, and why
unslop 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
97% identical to unslop — 49 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unslop
Edit text to remove AI patterns and add human voice.
Process
- Scan for the patterns below.
- Rewrite. Preserve meaning, match intended tone.
- Add soul (see next section).
- Self-audit: "What makes this obviously AI generated?" Fix remaining tells.
Adding soul
Removing patterns is half the job. Sterile, voiceless writing is just as obvious.
- Have opinions. React to facts instead of neutrally listing pros and cons.
- Vary rhythm. Short sentences. Then longer ones that take their time. Mix it up.
- Acknowledge complexity. "Impressive but also kind of unsettling" beats "impressive."
- Use "I" when it fits. First person isn't unprofessional.
- Let some mess in. Perfect structure looks machine-made.
- Be specific. Not "this is concerning" but "there's something unsettling about agents churning away at 3am."
Patterns to detect and fix
Content
- Puffery. "pivotal moment", "testament to", "evolving landscape", "setting the stage for", "indelible mark", "deeply rooted". Cut puffery, state what happened.
- Name-dropping. Listing media outlets without context. Pick one, say what was said.
- Superficial -ing phrases. "highlighting...", "ensuring...", "reflecting...", "showcasing...", "fostering...". Delete or expand with real sources.
- Promotional language. "nestled", "vibrant", "breathtaking", "groundbreaking", "renowned", "stunning", "must-visit". Use neutral descriptions.
- Vague attributions. "Experts believe", "Industry reports suggest", "Some critics argue". Name the source or delete.
- Formulaic challenges. "Despite challenges... continues to thrive." Replace with specific facts.
Language
- AI vocabulary. Additionally, crucial, delve, enduring, enhance, fostering, garner, interplay, intricate, landscape (abstract), pivotal, showcase, tapestry (abstract), testament, underscore, vibrant. Replace with plain words.
- Fancy ways to say "is". "serves as", "stands as", "boasts", "features". Just say "is" or "has".
- "Not just X, but Y." State the point directly instead.
- Rule of three. Forcing ideas into groups of three. Use the natural number.
- Synonym cycling. Protagonist, main character, central figure, hero all in one paragraph. Pick one, repeat it.
- False ranges. "from X to Y" where X and Y aren't on a meaningful scale. List topics directly.
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 · 81 lines · 14 tokens per session scan A 4474b7bfe4cb
unslop is a skill published in the GitHub repository painhardcore/pstack (12 stars, last pushed 9d ago), licensed MIT. It adds 14 tokens to every session and 1,620 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to unslop, differing in 49 lines, and is treated as a copy.
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