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 dailyaiagents-cpu/dailyai-os --skill public-content-scrubbergit clone --depth 1 https://github.com/dailyaiagents-cpu/dailyai-osWrote 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/dailyaiagents-cpu/dailyai-os/public-content-scrubber)<a href="https://agentmods.dev/skills/dailyaiagents-cpu/dailyai-os/public-content-scrubber"><img src="https://agentmods.dev/badge/skills/dailyaiagents-cpu/dailyai-os/public-content-scrubber/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/dailyaiagents-cpu/dailyai-os/public-content-scrubber"><img src="https://agentmods.dev/badge/skills/dailyaiagents-cpu/dailyai-os/public-content-scrubber.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 | $0.00080 | $0.00889 |
| Opus 5 | $0.00040 | $0.00445 |
| Sonnet 5 | $0.00016 | $0.00178 |
| Haiku 4.5 | $0.00008 | $0.00089 |
Grade A, and why
public-content-scrubber 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 12d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
public-content-scrubber
What this catches
The privacy posture is Stripe Press / Linear / Anthropic — quality of artifact in public, financial detail private. This scrubber is the structural enforcement of that posture across every public surface (newsletters, ship logs, sales pages, founder letters, Reddit/LinkedIn drafts, brief issues, site copy).
It blocks four categories of accidental leak:
- Dollar amounts —
$5,000,$1.2M,$500/mo(unless the trailing context names a known pricing/methodology word likemax position,daily exposure,starter,pro,tier) - Financial terms — MRR, ARR, revenue, P&L, profit, commission, bankroll, fills, win rate, edge realized, drawdown, Sharpe (unless context contains
target,spec,threshold,min,max,goal,floor,cap— these signal methodology, not actual performance) - Customer counts — exact figures: "47 paying users", "200 subscribers"
- Trading profile URLs —
kalshi.com/profile/<user>(track record stays NDA-only)
When to use
Wired into every public-output skill BEFORE publish:
- newsletter-weekly-publish
- ship-log-publish
- founder-letter-publish
- sales-page-edit
- product-page-edit
- reddit-outreach-paced
- linkedin-outreach-paced
- brief-publish
- site/index.html or any site/* edit
Pattern: drafter generates → scrubber scans → on hit, drafter rewrites → scrubber scans again → on clean, voice-gate runs (advisory) → publish.
Procedure
python3 ${REPO_ROOT}/tools/voice/scrubber.py "$DRAFT_PATH"
EXIT=$?
if [ $EXIT -eq 0 ]; then
echo "STATUS=clean"
elif [ $EXIT -eq 1 ]; then
echo "STATUS=blocked"
echo "$(cat /dev/stdin)" | python3 ${REPO_ROOT}/tools/voice/scrubber.py - > /tmp/scrubber-hits.json
# Surface hits to drafter for revision
fi
Exit 0 = clean, exit 1 = hits found (block publish), exit 2 = bad input.
Hard rules
- Never bypass. Every public output goes through. False positives are acceptable; false negatives are unrecoverable.
- Cooper override only. If the drafter believes a hit is a false positive, the workflow opens an approval gate
OVERRIDE_SCRUBBER_<reason>. Cooper YES → publish proceeds with the hit on record. NO → revise. - Keep updating allowlists conservatively. New legit pricing tiers / methodology values get added to
tools/voice/scrubber.pyPRICING_CONTEXT regex. Each addition is a commit Cooper reviews. - Pair with voice-gate. The scrubber blocks; voice-gate advises. Both run; both findings surface.
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.
- 12d ago First seen · 77 lines · 80 tokens per session scan A 59a6efbc2c45
public-content-scrubber is a skill published in the GitHub repository dailyaiagents-cpu/dailyai-os (0 stars, last pushed 4mo ago), licensed MIT. It adds 80 tokens to every session and 889 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…