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 agentmods add skills/ehmo/slopkit/slopbethnpx skills add ehmo/slopkit --skill slopbethgit clone --depth 1 https://github.com/ehmo/slopkitWhat 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 | $0.00065 | $0.01566 |
| Opus 5 | $0.00032 | $0.00783 |
| Sonnet 5 | $0.00013 | $0.00313 |
| Haiku 4.5 | $0.00006 | $0.00157 |
Grade A, and why
slopbeth 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 2d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slopbeth
Remove machine-writing tells without sanding away the author's meaning or voice. The target is not "detector-proof" prose; it is dense, specific writing where every sentence carries load and detector results stay dated and tool-specific.
Workflow
- Classify the task: rewrite; critique; benchmark; detector-facing validation; or skill maintenance.
- Separate the brief from the artifact. Long inputs often mix the material with instructions about it: "the note should keep that texture"; "do not turn this into a lesson"; "the rewrite must not promise that the problem cannot recur". Those sentences address you, not the reader. Do what they ask and leave them out of the output. Reprinting them is the same class of error as inventing content, and preservation and density checks will not catch it, because instruction text is specific, sourced, and dense.
- Preserve facts first. Lock named entities; numbers; dates; URLs; citations; quotations; technical claims; explicit uncertainty; and the user's requested stance.
- Set the evidence boundary. When the user supplies only vague copy, switch to evidence-bound mode: do not invent or assert product features; dates; people; metrics; workflows; examples; customer facts; or outcome claims. Unsupported claims such as "faster decisions," "better alignment," "reduced friction," "confidence," or "momentum" must become proof gaps, questions, or explicitly attributed claims.
- Diagnose clusters, not isolated words. Look for filler; vague significance language; formulaic contrast; promotional inflation; padded lists; generic uplift; actorless claims; summary endings; and ornamental formatting.
- Rewrite in this order: preserve claims and constraints; cut scaffolding and inflated abstract nouns; apply Orwell's six rules as generation defaults (short word over long, cut deletable words, active over passive, no printed-cliche metaphor or jargon, but break any rule sooner than write something unclear or graceless); make each sentence carry a claim, example, constraint, image, number, consequence, or argumentative move; match the user's register; remove concrete details that are not sourced or clearly labeled; check for meaning loss, bland-clean prose, formula replacement, and over-editing.
- Validate when files or before/after text are available. Use the scripts in
scripts/for repeatable checks, then apply judgment for meaning, voice, and sentence-load failures. - Output the revised text first for normal rewrite requests. Add a compact note only when it helps explain material changes, preservation risks, or remaining issues.
What ships with it
46 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/claude-code.yaml 202 B
- agents/codex.yaml 202 B
- agents/hermes.yaml 202 B
- agents/openai.yaml 202 B
- agents/openclaw.yaml 202 B
- agents/opencode.yaml 202 B
- agents/pi.yaml 202 B
- assets/slopbeth.png 1464 KB
- BENCHMARKS.md 5.3 KB
- benchmarks/benchmark-v2.jsonl 74 KB
- benchmarks/competitor-agent-runs-v1.jsonl 32 KB
- benchmarks/competitor-matrix-v2.md 3.8 KB
- benchmarks/competitor-output-runs-v1.jsonl 8.3 KB
- benchmarks/false-positive-tracker-v1.jsonl 3.9 KB
- benchmarks/independent-judge-rows-v2.jsonl 90 KB
- benchmarks/orwell-writing-system-v1.jsonl 8.3 KB
- benchmarks/public-detector-panel-v1.md 1.2 KB
- benchmarks/README.md 1.7 KB
- benchmarks/score-snapshot.md 4.1 KB
- benchmarks/span-annotations-v1.jsonl 6.3 KB
- CONTRIBUTING.md 1.1 KB
- docs/branch-protection.md 1.1 KB
- docs/creation-and-validation.md 1.8 KB
- docs/false-positive-tracker.md 1.3 KB
- docs/literature-basis.md 3.8 KB
- README.md 5.6 KB
- references/density-and-unsummarizability.md 1.6 KB
- references/evaluation.md 3.1 KB
- references/slop-taxonomy.md 2.9 KB
- references/voice-and-preservation.md 4.1 KB
- references/writing-system.md 5.4 KB
- scripts/cadence_score.py 5.1 KB runs code
- scripts/competitor_output_score.py 13 KB runs code
- scripts/density_report.py 2.8 KB runs code
- scripts/deslop_lint.py 5.5 KB runs code
- scripts/false_positive_check.py 4.0 KB runs code
- scripts/orwell_benchmark.py 7.0 KB runs code
- scripts/orwell_lint.py 12 KB runs code
- scripts/preservation_check.py 2.9 KB runs code
- scripts/run_benchmark.py 15 KB runs code
- scripts/semantic_drift.py 17 KB runs code
- scripts/signature_score.py 16 KB runs code
- scripts/span_annotation_check.py 4.9 KB runs code
- scripts/unsummarizability_check.py 14 KB runs code
- SECURITY.md 320 B
- SUPPORT.md 289 B
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.
- 2d ago First seen · 68 lines · 65 tokens per session scan A dfb2d461b8c4
slopbeth is a skill published in the GitHub repository ehmo/slopkit (96 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,566 once invoked, about $0.0003 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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