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 hani-q/qstack --skill qstack-unslopgit clone --depth 1 https://github.com/hani-q/qstackWrote 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/hani-q/qstack/qstack-unslop)<a href="https://agentmods.dev/skills/hani-q/qstack/qstack-unslop"><img src="https://agentmods.dev/badge/skills/hani-q/qstack/qstack-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/hani-q/qstack/qstack-unslop"><img src="https://agentmods.dev/badge/skills/hani-q/qstack/qstack-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 | $0.00027 | $0.01348 |
| Opus 5.5 | $0.00011 | $0.00539 |
| Sonnet 5.5 | $0.00005 | $0.00270 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
qstack-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.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/qstack-unslop
Rewrite the immediately previous assistant answer. Output only the rewrite.
Process
- Scan for the patterns below.
- Rewrite while preserving meaning, useful detail, technical accuracy, and the intended tone. Do not shorten merely for the sake of shortening.
- Add human voice where it fits.
- Ask, "What makes this obviously AI generated?" Fix the remaining tells.
Do not add facts, claims, decisions, or recommendations. Keep file paths, commands, warnings, and next actions when the reader still needs them. Do not repeat the work or call tools.
If there is no previous substantive assistant answer, say so in one short line.
Human voice
- Have opinions when judgment is useful. React to facts instead of mechanically listing pros and cons.
- Vary rhythm. Mix short sentences with longer ones when the idea needs room.
- Acknowledge real complexity instead of flattening every reaction.
- Use "I" when it fits. First person is not unprofessional.
- Allow natural asymmetry. Perfectly repeated structure looks manufactured.
- Be specific. Replace a vague feeling with the fact that causes it.
Patterns to fix
Content
- Puffery. Cut phrases such as "pivotal moment", "testament to", "evolving landscape", "setting the stage for", "indelible mark", and "deeply rooted." State what happened.
- Name-dropping. Do not list media outlets without context. Pick the relevant source and say what it reported.
- Superficial -ing phrases. Delete or substantiate phrases such as "highlighting", "ensuring", "reflecting", "showcasing", and "fostering."
- Promotional language. Replace "nestled", "vibrant", "breathtaking", "groundbreaking", "renowned", "stunning", and "must-visit" with neutral descriptions.
- Vague attributions. Name the source behind "experts believe", "industry reports suggest", or "some critics argue", or delete the claim.
- Formulaic challenges. Replace "despite challenges, it continues to thrive" with the specific facts.
What ships with it
1 file 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 · 120 lines · 27 tokens per session scan A d4ecc5d11907
qstack-unslop is a skill published in the GitHub repository hani-q/qstack (7 stars, last pushed 3d ago), licensed MIT. It adds 27 tokens to every session and 1,348 once invoked, about $0.0001 per session on Opus 5.5. 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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