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 wpgaurav/claude-code-skills --skill slop-detectorgit clone --depth 1 https://github.com/wpgaurav/claude-code-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/wpgaurav/claude-code-skills/slop-detector)<a href="https://agentmods.dev/skills/wpgaurav/claude-code-skills/slop-detector"><img src="https://agentmods.dev/badge/skills/wpgaurav/claude-code-skills/slop-detector/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/wpgaurav/claude-code-skills/slop-detector"><img src="https://agentmods.dev/badge/skills/wpgaurav/claude-code-skills/slop-detector.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 | $0.00096 | $0.01401 |
| Opus 5.5 | $0.00038 | $0.00560 |
| Sonnet 5.5 | $0.00019 | $0.00280 |
| Haiku 4.5 | $0.00010 | $0.00140 |
Grade A, and why
slop-detector 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slop Detector
Audit prose for AI slop and report findings by severity. Stop Slop tells a model what not to write; this skill checks what was written and says how bad it is.
A banned-words list fails in both directions. It flags "robust" in a sentence about a nonce implementation, and it passes a caption that says "a fresh capture, not a generic mockup." The severity model below separates the two.
Severity model
slop-detector.json in this folder is the authority. Four tiers:
| Severity | Meaning | What to do |
|---|---|---|
hard_fail |
Exact, high-confidence production or process narration in reader-facing copy ("captured with Playwright", "Status in this study", "Weak spot: I didn't test") | Block publication and rewrite. A low score never rescues a hard fail. |
warn_if_repeated |
Rhetorical scaffolds that can carry one real turn: mirrored "not X, it's Y" contrasts, "No X. No Y. No Z." triads, per-item disclaimers, templated roundup filler | Count across the piece. Warn only at the family's repeat threshold. |
contextual_review |
Broad lexical signals: "leverage", "seamless", "here's the thing", academic connectors, empty intensifiers | Read the sentence. Quotations, code, proper names, and precise technical terms are not defects. Never auto-replace. |
structural_diagnostic |
Document-level patterns: identical paragraph lengths, a dead table column, the same sentence closing every item, passive-voice density | Diagnose the cause. Never add fragments, emotion, or asymmetry to make a metric pass. |
Advisory score, counted only after context review: warn_if_repeated +2, confirmed contextual_review +1, structural_diagnostic +3, +2, or +1 by priority.
- 0 to 5: clean
- 6 to 15: needs editing
- 16+: rewrite the affected passages or structure
Truth, source fidelity, and authorial intention sit above this model. An unsupported claim or invented first-person experience blocks publication even when the score is 0.
Workflow
What ships with it
7 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.
- 1mo ago First seen · 91 lines · 96 tokens per session scan A 8cee68830ad8
slop-detector is a skill published in the GitHub repository wpgaurav/claude-code-skills (3 stars, last pushed 2d ago), licensed MIT. It adds 96 tokens to every session and 1,401 once invoked, about $0.0004 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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