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Citation monitor

Skill waseemnasir2k26/skynetlabs-all-claude-code/skills/seo-content-copy/citation-monitor

44 production Claude Code skills — content & reels, SEO/AEO, client delivery, code review, planning, token efficiency. One-command install.

Install

npx -y skills add waseemnasir2k26/skynetlabs-all-claude-code --skill citation-monitor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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What its author says it does

Copied from the file, not written here

Track brand mention citations across 4 LLMs (Claude, ChatGPT, Perplexity, Gemini) for a configurable list of brand keywords. Daily cron pulls write to local sqlite. Weekly markdown report shows mention counts, position, and citation deltas. Powers citelift.app SaaS upgrade path. Local-first; Supabase + n8n optional later.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

3.7 KB, as published. Nobody here has run it

citation-monitor v0.1.0

Purpose

Answer the question: "Is my brand showing up when buyers ask LLMs for recommendations?"

Daily, query 4 LLMs with a fixed prompt set per tracked brand. Score each response for brand mention, list position, and citation URL presence. Store in sqlite. Render a weekly markdown report with deltas.

Architecture (v0.1.0 — local-first)

Layer	Implementation
Inputs	`tracked-brands.json` (brand + keywords + niche)
Engines	Claude (full), OpenAI (full), Perplexity (stub), Gemini (stub)
Storage	sqlite at `data/citations.db`
Schedule	cron-friendly entry point `scripts/run_daily.py`
Reports	`reports/<yyyy-ww>.md` markdown with deltas

Upgrade path (v0.2+): Supabase Postgres + n8n cron + multi-tenant brand list.

Schema (sqlite)

citations(
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  brand TEXT NOT NULL,
  keyword TEXT NOT NULL,
  engine TEXT NOT NULL,
  query TEXT NOT NULL,
  response_excerpt TEXT,
  mention_count INTEGER DEFAULT 0,
  position INTEGER,           -- 1-indexed list position; NULL if not mentioned
  citation_url TEXT,
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)

Execution Flow

Init (one-time) — python scripts/init_db.py creates data/citations.db.
Daily run — python scripts/run_daily.py reads tracked-brands.json, loops brand x keyword x engine x prompt-template, calls each engine, scores response, inserts row.
Weekly report — python scripts/weekly_report.py reads sqlite, computes week-over-week deltas, writes reports/<yyyy-ww>.md.

Triggers in conversation

When the user says any of:

"track citations for SkynetLabs"
"run citation monitor"
"weekly AEO report"
/citation-monitor

Read tracked-brands.json, run scripts/run_daily.py, then offer to render the weekly report.

Cost guardrails

Default model IDs: claude-haiku-4-5 and gpt-4o-mini. Cheapest tier per provider.
Anthropic prompt caching enabled (5-min ephemeral) on the system prompt — every brand+keyword tuple shares the system prompt, so cache hit rate is high.
One run = ~24 API calls (3 brands x 2 engines x 4 prompts). At Haiku + Mini pricing, approximately $0.01-0.03/day.

Constraints

No fake-claims content. No em-dashes in any output.
v0.1 ships Claude + OpenAI fully. Perplexity + Gemini raise NotImplementedError with a clear v0.2 — needs <KEY> message.
Python 3.11+. Pinned deps in requirements.txt.

Files

SKILL.md — this file
README.md — quick start
requirements.txt — pinned deps
.env.example — required env vars
tracked-brands.example.json — input shape
scripts/init_db.py — sqlite schema
scripts/run_daily.py — main loop
scripts/query_engines.py — engine abstractions
scripts/weekly_report.py — markdown report
references/prompt-templates.md — exact prompts
references/aeo-scoring-rubric.md — scoring math
data/.gitkeep, reports/.gitkeep

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