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 holoviz-dev/holoviz-skills --skill deslopgit clone --depth 1 https://github.com/holoviz-dev/holoviz-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/holoviz-dev/holoviz-skills/deslop)<a href="https://agentmods.dev/skills/holoviz-dev/holoviz-skills/deslop"><img src="https://agentmods.dev/badge/skills/holoviz-dev/holoviz-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/holoviz-dev/holoviz-skills/deslop"><img src="https://agentmods.dev/badge/skills/holoviz-dev/holoviz-skills/deslop.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 | $0.00061 | $0.01673 |
| Opus 5.5 | $0.00024 | $0.00669 |
| Sonnet 5.5 | $0.00012 | $0.00335 |
| Haiku 4.5 | $0.00006 | $0.00167 |
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 16d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deslop
Remove the recognisable machinery of LLM prose from a piece of writing without changing what it says.
Two failure modes to avoid, in order of severity:
- Changing the meaning. The point is to delete the performance, not the content. If a slop pattern is wrapped around a real claim, keep the claim and drop the wrapper.
- Trading one tic for another. A rewrite that swaps "here's the thing" for "the reality is" has done nothing. Prefer deletion over substitution.
Before drafting
The rest of this skill cleans up a finished draft. When you're the one drafting a PR description, a docs page or a blog post, these keep most slop out of the first draft:
- Ask for a sample of the author's writing, or a piece they want to sound like, and match it. Models imitate an example far more reliably than they follow adjectives like "concise" or "natural".
- Name the reader before writing ("maintains a Panel app", "has never used HoloViews"). The reader decides what needs explaining.
- Describe the voice you want instead of listing tics to avoid. Naming a tic tends to make it show up.
The HoloViz voice, which the pr-description, documentation and outreach skills build on:
- Write in the first person, as the person who did the work, including what went wrong.
- Join cause and effect in one sentence with the connective that relates them (since, so, but) instead of a run of short beats, and vary the length. Joining can trade a
[choppy-run]for a[justification-tail]once every sentence ends the same way, and a rescan catches that. - Make each point once, and keep the concrete anchors (identifiers, numbers, a minimal example) while compressing.
- Use the word you'd say out loud to a colleague.
Workflow
1. Identify the target. A file path, a range in a file, or a draft sitting in the conversation. If the user says "deslop this" with no target, use the most recent substantial prose in the conversation. If the target is ambiguous between two candidates, ask.
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.
- 16d ago Changed · -1 lines 5b2f7f845927
- 21d ago Changed · +2 lines c335e72c2fba
- 1mo ago Changed · +15 lines f06f59d9b7b3
- 1mo ago Changed 837c00a8bf25
- 1mo ago Changed 2653b01c593c
- 1mo ago First seen · 67 lines · 61 tokens per session scan A 293667ba9ecc
deslop is a skill published in the GitHub repository holoviz-dev/holoviz-skills (5 stars, last pushed 2d ago), licensed BSD-3-Clause. It adds 61 tokens to every session and 1,673 once invoked, about $0.0002 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 2026-09-09.
deslop compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deslopholoviz-dev/holoviz-skills | Skill | 5 | 2d ago | BSD-3-Clause | A | 61 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |