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 sergekostenchuk/ui-ux-agent-skill-system --skill llm-citation-monitorgit clone --depth 1 https://github.com/sergekostenchuk/ui-ux-agent-skill-systemWrote 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/sergekostenchuk/ui-ux-agent-skill-system/llm-citation-monitor)<a href="https://agentmods.dev/skills/sergekostenchuk/ui-ux-agent-skill-system/llm-citation-monitor"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/llm-citation-monitor/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/sergekostenchuk/ui-ux-agent-skill-system/llm-citation-monitor"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/llm-citation-monitor.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 | $0.00084 | $0.00827 |
| Opus 5 | $0.00042 | $0.00413 |
| Sonnet 5 | $0.00017 | $0.00165 |
| Haiku 4.5 | $0.00008 | $0.00083 |
Grade A, and why
llm-citation-monitor 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.
This is a copy
100% identical to llm-citation-monitor — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Citation Monitor
Use this skill after the target site's SEO/LLM discovery layer exists and the user wants to measure assistant/search citation visibility.
Read references/citation-evidence-policy.md before producing a monitoring plan or report.
Owns
- target question matrix;
- manual observation workflow;
- citation report template;
- assistant/search surface evidence policy;
- competitor citation capture;
- caveats for personalization, locale, freshness, and account state;
- refusal of unsupported citation claims.
Does Not Own
- assistant account credentials;
- bypassing bot protections;
- scraping assistant/search surfaces without approval;
- changing robots, WAF, auth, or crawler policy;
- ranking claims;
- content/schema implementation.
Workflow
- Define target site, page set, audience, locale, and target questions.
- Classify query intent: brand, topic, problem, comparison, how-to, or citation-check.
- Choose approved observation mode: manual, exported transcript, screenshot, API/tool report, or public fetch.
- For each run, record surface, model/search product if visible, date/time, locale, account state, query text, answer summary, cited URLs, quote/snippet, and caveats.
- Capture competitor citations separately from target citations.
- Mark missing citations as
not observed, not as "does not cite anywhere". - Produce a report using assets/citation-report.template.md.
- Hand off site-content or technical fixes to SEO/LLM architecture skills.
Non-Negotiables
- Do not claim "ChatGPT cites us" without direct citation evidence.
- Do not treat one personalized answer as universal ranking.
- Do not store assistant credentials, cookies, account tokens, or private conversation data in skill files.
- Do not bypass paywalls, auth, robots, WAF, or tool restrictions.
- Do not scrape surfaces against terms of service.
- Do not publish screenshots/transcripts containing private user data.
What ships with it
5 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.
- 12d ago First seen · 89 lines · 84 tokens per session scan A f1f0fe1c5e61
llm-citation-monitor is a skill published in the GitHub repository sergekostenchuk/ui-ux-agent-skill-system (23 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 827 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to llm-citation-monitor, differing in 4 lines, and is treated as a copy.
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