Install
$ agentstack add skill-sergekostenchuk-ui-ux-agent-skill-system-llm-citation-monitor ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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](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](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.
Safety And Privacy Boundaries
- Reports should contain only approved public query text, public cited URLs, and redacted/private-safe snippets.
- If a screenshot or transcript includes account details, remove them before adding to shared artifacts.
- If a user provides a private assistant transcript, summarize it locally and ask before storing it.
- Treat model version, locale, date/time, and account state as part of the evidence, not incidental metadata.
Evidence Labels
Cited: target URL appears as a cited/source URL in the answer or citation panel.Mentioned: target brand/page mentioned but not cited.Not observed: no target citation in this run.Competitor cited: another domain was cited for the target question.Invalid evidence: missing timestamp, surface, query, or cited URL.
Validation
Validate skill edits with:
python3 $CODEX_HOME/skills/senior-skill-architect/scripts/lint_production_skill.py $HOME/SKILL/skills/llm-citation-monitor
python3 $HOME/SKILL/plans/seo-llm-skill-cluster/scripts/lint_skill_cluster.py $HOME/SKILL
Forward tests live in [evals.json](evals.json).
Output Shape
Return:
- Monitoring objective and target pages.
- Query matrix.
- Approved surfaces and observation mode.
- Citation evidence table.
- Competitor citation table.
- Caveats and limitations.
- Fix backlog routed to the correct skill owner.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: sergekostenchuk
- Source: sergekostenchuk/ui-ux-agent-skill-system
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.