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 prashishh/seo-geo-report-engine --skill ai-citation-sprintgit clone --depth 1 https://github.com/prashishh/seo-geo-report-engineWrote 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/prashishh/seo-geo-report-engine/ai-citation-sprint)<a href="https://agentmods.dev/skills/prashishh/seo-geo-report-engine/ai-citation-sprint"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/ai-citation-sprint/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/prashishh/seo-geo-report-engine/ai-citation-sprint"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/ai-citation-sprint.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 | $0.00135 | $0.01313 |
| Opus 5 | $0.00068 | $0.00656 |
| Sonnet 5 | $0.00027 | $0.00263 |
| Haiku 4.5 | $0.00014 | $0.00131 |
Grade A, and why
ai-citation-sprint 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.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-citation-sprint
Orchestrate a product's path from "AI systems do not know or cite us" to a measured, defensible AI-search presence. This skill is inspired by public AEO agency patterns such as AEO Engine's managed execution model: audit, prompt mapping, source pages, schema/entity fixes, authority signals, and weekly measurement. Keep using Ahrefs/Brand Radar until the framework's replacement provider layer is finalized.
Core Principle
Do not stop at a diagnostic report. Every sprint must create or improve assets that AI systems can
actually cite: source pages, comparison pages, proof pages, schemas, llms.txt, internal links,
third-party corroboration, and measurement logs.
CITE+ Framework
Score every project across five pillars:
- Coverage — Does the brand appear across the prompts, SERPs, directories, communities, and third-party sources where AI systems look?
- Indexability — Are the canonical pages crawlable, internally linked, included in sitemaps, and free of robots/canonical/schema blockers?
- Trust — Are claims backed by reviews, case studies, named people, citations, credentials, and credible third-party mentions?
- Entity — Is the brand clearly defined: who it serves, what category it belongs to, what it offers, and how it differs from alternatives?
- Extraction — Are pages structured so AI can lift the answer: direct definitions, tables, FAQs, HowTo steps, sourced statements, and schema matching visible text?
Workflow
1. PERCEIVE — baseline visibility
- Resolve project:
./bin/mkt config show --project <client>. - Read
client.yml,BUILD-STATUS.md, existing research, and deliverables. - Use Ahrefs MCP per
knowledge/ahrefs-mcp-map.md:- Brand Radar for mentions, share of voice, cited domains/pages, AI responses.
- Rank Tracker and SERP overview for search visibility.
- Site Audit / Site Explorer for crawl and authority context.
- If Brand Radar is not configured, create a manual prompt grid and append to
projects/<client>/data/ai-citation-log.csv. Run that grid live with theweb-researchskill's probe mode (OpenRouter,perplexity/sonar) — it costs a fraction of a cent per prompt, so the whole grid is cheap to run on a schedule even without Brand Radar.
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 · 121 lines · 135 tokens per session scan A f55898f89e78
ai-citation-sprint is a skill published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 135 tokens to every session and 1,313 once invoked, about $0.0007 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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