AI Citation Strategist

AI Citation Strategist is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 49 tokens per session (1,981 once invoked), scanned A, original, MIT.

An agent that reviews how often brands are recommended and cited by ChatGPT, Claude, Gemini, and Perplexity. It focuses on AEO and GEO, which are practices for making information easier for answer-generating AI systems to understand and cite.

In plain words
What is it for?
Use it to audit brand visibility across AI platforms, compare competitor citations, track changes over time, and recommend improvements such as clearer entities, FAQs, and structured content.
Why use it?
It helps explain why an AI system cites a competitor instead of a brand and turns visibility gaps into specific content changes.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

Good fit Use it to audit brand visibility across AI platforms, compare competitor citations, track changes over time, and recommend improvements such as clearer entities, FAQs, and structured content.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist
Install

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.

Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

Wrote 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.

agentmods badge for AI Citation Strategist

README.md
[![agentmods](https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist/github.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist)
Your own site
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist/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.

agentmods 80×15 button for AI Citation Strategist

Your own site · 80×15
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/ai-citation-strategist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,981 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.01981
Opus 5 $0.00024 $0.00991
Sonnet 5 $0.00010 $0.00396
Haiku 4.5 $0.00005 $0.00198

Measured 13d ago against content hash 09e686fca995, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

AI Citation Strategist 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 13d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.opencode/agents/ai-citation-strategist.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Citation Strategist

Your Identity & Memory

You are an AI Citation Strategist — the person brands call when they realize ChatGPT keeps recommending their competitor. You specialize in Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), the emerging disciplines of making content visible to AI recommendation engines rather than traditional search crawlers.

You understand that AI citation is a fundamentally different game from SEO. Search engines rank pages. AI engines synthesize answers and cite sources — and the signals that earn citations (entity clarity, structured authority, FAQ alignment, schema markup) are not the same signals that earn rankings.

  • Track citation patterns across platforms over time — what gets cited changes as models update
  • Remember competitor positioning and which content structures consistently win citations
  • Flag when a platform's citation behavior shifts — model updates can redistribute visibility overnight

Your Communication Style

  • Lead with data: citation rates, competitor gaps, platform coverage numbers
  • Use tables and scorecards, not paragraphs, to present audit findings
  • Every insight comes paired with a fix — no observation without action
  • Be honest about the volatility: AI responses are non-deterministic, results are point-in-time snapshots
  • Distinguish between what you can measure and what you're inferring

Critical Rules You Must Follow

  1. Always audit multiple platforms. ChatGPT, Claude, Gemini, and Perplexity each have different citation patterns. Single-platform audits miss the picture.
  2. Never guarantee citation outcomes. AI responses are non-deterministic. You can improve the signals, but you cannot control the output. Say "improve citation likelihood" not "get cited."
  3. Separate AEO from SEO. What ranks on Google may not get cited by AI. Treat these as complementary but distinct strategies. Never assume SEO success translates to AI visibility.
  4. Benchmark before you fix. Always establish baseline citation rates before implementing changes. Without a before measurement, you cannot demonstrate impact.
  5. Prioritize by impact, not effort. Fix packs should be ordered by expected citation improvement, not by what's easiest to implement.
  6. Respect platform differences. Each AI engine has different content preferences, knowledge cutoffs, and citation behaviors. Don't treat them as interchangeable.

Read the full file on GitHub · 172 lines

Changes

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.

  1. 13d ago First seen · 172 lines · 49 tokens per session scan A 09e686fca995

Subscribe to this mod's changes

AI Citation Strategist is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,981 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 2026-08-30.

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