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 patrick-fu/awesome-skills --skill deslopgit clone --depth 1 https://github.com/patrick-fu/awesome-skillsWrote 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/patrick-fu/awesome-skills/deslop)<a href="https://agentmods.dev/skills/patrick-fu/awesome-skills/deslop"><img src="https://agentmods.dev/badge/skills/patrick-fu/awesome-skills/deslop/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/patrick-fu/awesome-skills/deslop"><img src="https://agentmods.dev/badge/skills/patrick-fu/awesome-skills/deslop.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 | $0.00117 | $0.01910 |
| Opus 5 | $0.00059 | $0.00955 |
| Sonnet 5 | $0.00023 | $0.00382 |
| Haiku 4.5 | $0.00012 | $0.00191 |
Grade A, and why
deslop 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deslop / 说人话
Edit existing prose so it sounds like a person making deliberate choices in a specific context, not a model performing “human” style. Preserve truth before style. A slightly awkward faithful sentence is better than a fluent invention.
This is an editorial skill, not an AI detector. Never assign an AI probability, promise detector evasion, or treat one word or punctuation mark as proof of authorship.
Route the request
Choose one delivery mode:
- Rewrite — default. Return one ready-to-use revision.
- Audit — only when the user asks to inspect, review, mark, or explain problems before rewriting. Report findings; do not silently rewrite.
- Embedded — when another workflow needs prose as an intermediate result. Return only the final text, without process notes. If ambiguity remains, preserve the more conservative source wording instead of guessing.
- File — only when the user explicitly asks to edit a file. Modify prose in place while preserving protected file regions, then summarize the change.
A user-provided writing sample or an explicitly maintained author preference layer adds voice calibration to any mode. It does not create a separate mode and never relaxes factual fidelity. Never infer, create, or update a persistent author profile from the current text.
Choose an edit scope:
- balanced — default. Reshape short text freely without deleting unique information. In long text, also preserve headings, paragraph roles, and argument order. Remove only demonstrably empty scaffolding.
- in-place — when the user asks to keep the structure, sentence count, or layout. Rewrite within sentences; do not delete, merge, or reorder them. If a sentence contains only slop, keep an awkward source-faithful shell or the original sentence rather than inventing a concrete object or outcome.
- rebuild — only when the user explicitly asks for a substantial rewrite, compression, or reorganization. Preserve the semantic ledger even when the shape changes.
What ships with it
21 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.
- agents/openai.yaml 266 B
- automation/eval/check_cases.py 4.7 KB runs code
- automation/eval/judge-prompt.md 773 B
- automation/eval/make_blind.py 1.9 KB runs code
- automation/eval/README.md 1.8 KB
- automation/eval/rewrite-prompt.md 917 B
- evals/benchmark-blind.json 15 KB
- evals/benchmark-map.json 16 KB
- evals/cases.json 29 KB
- evals/rubric.md 2.7 KB
- evals/triggers.json 3.4 KB
- LICENSE 1.0 KB
- NOTICE.md 2.1 KB
- README.md 1.9 KB
- README.zh-CN.md 1.7 KB
- references/boundary-cases.md 4.1 KB
- references/fidelity.md 7.8 KB
- references/patterns-en.md 5.7 KB
- references/patterns-zh.md 11 KB
- references/scenes.md 4.6 KB
- references/voice-calibration.md 3.3 KB
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 · 179 lines · 117 tokens per session scan A c306e82a9a53
deslop is a skill published in the GitHub repository patrick-fu/awesome-skills (58 stars, last pushed 2d ago), licensed MIT. It adds 117 tokens to every session and 1,910 once invoked, about $0.0006 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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