Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add seyedehsanhadi/sloptrim/plugin install sloptrimWrote 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/seyedehsanhadi/sloptrim/sloptrim)<a href="https://agentmods.dev/skills/seyedehsanhadi/sloptrim/sloptrim"><img src="https://agentmods.dev/badge/skills/seyedehsanhadi/sloptrim/sloptrim/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/seyedehsanhadi/sloptrim/sloptrim"><img src="https://agentmods.dev/badge/skills/seyedehsanhadi/sloptrim/sloptrim.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 | $0.00114 | $0.04835 |
| Opus 5.5 | $0.00046 | $0.01934 |
| Sonnet 5.5 | $0.00023 | $0.00967 |
| Haiku 4.5 | $0.00011 | $0.00483 |
Grade A, and why
sloptrim 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 3d 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 — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sloptrim
Trims AI slop from text. Works a catalogue of 71 patterns: 62 machine-checked by scripts/detect.py, 9 requiring semantic judgment during the rewrite. Of the 62, 50 can move the score; the rest are reported as writing advice and count for nothing. Mode-aware so it does not invent voice on factual content. Preserves facts. Rebuilds the cleaned text toward a selectable human-voice style profile so it does not read as a sterile de-AI'd husk.
Silence
This skill never talks about itself. It hands back the cleaned text and nothing else.
Never emit: any announcement that sloptrim ran, style/mode lines, scores or reports, drafts, self-audit notes, facts-preserved lines, change lists, preambles, closing offers.
Emit only:
- Text given inline: the final text. Nothing before it, nothing after it.
- A file path given: rewrite the file in place, then one line - the path. Nothing else.
- Fired as a pre-delivery pass on something you were already writing (CV, cover letter, email, report, essay): just deliver the clean text. Do not mention that a pass happened.
Every internal step still runs - detector, tiering, self-audit, character scrub. Silence means nothing is printed, not that anything is skipped.
Break silence only for: (a) a fact you cannot preserve, or an unusual word you cannot verify against the domain - one line, then the text; (b) the user explicitly asking for the score, the report, a style choice, or a diff - then answer in full; (c) a high-stakes first-person deliverable - a cover letter, personal statement, or bio the user is about to send - where after the text you may add exactly one line offering a voice switch (for example: "Voice here is plain-professional; say the word for warmer or more formal."). One line, only for these high-stakes cases, never for routine prose.
Style, chosen silently
Never ask. Read the content and pick:
- encyclopedic / factual / technical → 2000s textbook
- first-person / opinion → conversational essay
- docs, README, business prose → plain / clear
- news → journalistic
What ships with it
11 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.
- assets/demo-dark.svg 58 KB
- assets/demo-light.svg 58 KB
- assets/detection-dark.svg 2.7 KB
- assets/detection-light.svg 2.7 KB
- assets/sloptrim-logo-dark.svg 46 KB
- assets/sloptrim-logo.svg 46 KB
- assets/social-preview.png 185 KB
- references/patterns.md 49 KB
- scripts/benchmark_frontier.py 6.0 KB runs code
- scripts/check_docs.py 33 KB runs code
- scripts/detect.py 96 KB runs code
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.
- 3d ago Changed f754d139a80c
- 20d ago Changed · +3 lines 73faee13a1ed
- 1mo ago Changed 8adedf0358d2
- 1mo ago First seen · 233 lines · 114 tokens per session scan A 4b6f40696c9e
sloptrim is a skill published in the GitHub repository seyedehsanhadi/sloptrim (408 stars, last pushed 4d ago), licensed Apache-2.0. It adds 114 tokens to every session and 4,835 once invoked, about $0.0005 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 2026-08-30.
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