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/contentscoin/qrcoding-skill-mcp/qrcoding-analyticsnpx skills add contentscoin/qrcoding-skill-mcp --skill qrcoding-analyticsgit clone --depth 1 https://github.com/contentscoin/qrcoding-skill-mcpWrote 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/contentscoin/qrcoding-skill-mcp/qrcoding-analytics)<a href="https://agentmods.dev/skills/contentscoin/qrcoding-skill-mcp/qrcoding-analytics"><img src="https://agentmods.dev/badge/skills/contentscoin/qrcoding-skill-mcp/qrcoding-analytics.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.00356 |
| Opus 5 | $0.00023 | $0.00178 |
| Sonnet 5 | $0.00009 | $0.00071 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
qrcoding-analytics 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.
What it actually says
QR Coding Analytics
"몇 명이 스캔했어", "추이 보여줘", "어느 지역/기기에서 봤어", "이번 주 성과" 같은 분석 요청을 분류한다. 실제 도구 호출은 qrcoding-campaign-operator로 위임한다.
분류 순서
- 총 스캔 / 마지막 스캔 시각 (한 QR 또는 워크스페이스 전체):
get_qr_analytics. - 상세 분석 — 일별 시계열, 기기(mobile/tablet/desktop/bot), 상위 국가, 상위 referrer 도메인:
get_qr_analytics_detail(선택:days윈도우).
위임 + 주의
- 분류가 끝나면 조회는
qrcoding-campaign-operator로 위임한다. - 집계값만 제공한다. 개별 스캐너의 신원/정확한 위치/IP는 저장하지 않는다.
- 국가·기기 분석은 수집 시작 이후의 스캔에만 존재한다(소급 불가). 데이터가 비어 있으면 이 점을 사용자에게 설명한다.
- 동적 QR만 스캔이 기록된다(정적 QR은 /r 리다이렉트가 없어 집계 대상이 아니다).
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 · 23 lines · 45 tokens per session scan A 45cf16c6bee3
qrcoding-analytics is a skill published in the GitHub repository contentscoin/qrcoding-skill-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 356 once invoked, about $0.0002 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.
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