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 calm-north/seojuice-claude-plugin --skill aiso-reportgit clone --depth 1 https://github.com/calm-north/seojuice-claude-pluginWrote 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/calm-north/seojuice-claude-plugin/aiso-report)<a href="https://agentmods.dev/skills/calm-north/seojuice-claude-plugin/aiso-report"><img src="https://agentmods.dev/badge/skills/calm-north/seojuice-claude-plugin/aiso-report/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/calm-north/seojuice-claude-plugin/aiso-report"><img src="https://agentmods.dev/badge/skills/calm-north/seojuice-claude-plugin/aiso-report.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 | $0.00817 |
| Opus 5 | $0.00042 | $0.00409 |
| Sonnet 5 | $0.00017 | $0.00163 |
| Haiku 4.5 | $0.00008 | $0.00082 |
Grade A, and why
aiso-report 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 11d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Search Optimization Report
Analyze how a website appears in AI-powered search results and how ready its content is for AI citation.
Instructions
-
Resolve the domain. If
$ARGUMENTSis provided, use it as the domain. If not, calllist_websitesand ask the user which site to analyze. -
Fetch AISO details. Call
get_aisowith:domain: the target domainperiod: "30d"include_history: true
-
Fetch intelligence summary for context. Call
get_intelligence_summarywith:domain: the target domainperiod: "30d"include_trends: true
-
Fetch website details for GEO data. Call
get_website_detailwith the domain to get avg_content_quality_score, avg_geo_readiness_score, and domain_health_score. -
Synthesize into an AISO report.
Output Format
AI Search Optimization: [domain]
AISO Composite Score: [score]/100
Sub-Scores
| Dimension | Score | Description |
|---|---|---|
| Visibility | [score] | How often the brand appears in AI responses |
| Sentiment | [score] | How positively the brand is mentioned |
| Position | [score] | Average position in AI response citations |
| Coverage | [score] | Breadth of topics where the brand appears |
| Competitive | [score] | How the brand compares to competitors in AI results |
Mention Statistics (last 30 days)
- Total mentions across AI platforms: [count]
- Brand mentions: [count]
- Brand mention rate: [percentage]
- Average position in AI responses: [avg_position]
- Positive sentiment rate: [positive_rate]
Content Readiness for AI
- Avg Content Quality (CORE-EEAT): [score]/100
- Avg GEO Readiness: [score]/100
- Domain Health: [score]/100
These scores indicate how well the site's content is structured for AI systems to understand, quote, and cite.
Historical Trend
Show AISO score trend over available months:
| Month | AISO Score | Trend |
|---|---|---|
| ... | ... | +/- change |
Context: SEO Health
- SEO Score: [score]
- Total Pages: [count]
- Content Gaps: [count]
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.
- 11d ago First seen · 88 lines · 84 tokens per session scan A 5ea672a5591b
aiso-report is a skill published in the GitHub repository calm-north/seojuice-claude-plugin (2 stars, last pushed 6mo ago), licensed MIT. It adds 84 tokens to every session and 817 once invoked, about $0.0004 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.
Other skills, from other repositories
content-amplifier
Use when the user asks to "amplify influencer content with paid media", "set up whitelisting or Spark Ads", "decide which posts to boost", "repurpose influencer content", "turn one video into multiple ads", or "build a UGC asset library"; produces (paid mode) a content-selection scorecard, a paid amplification…
email-sequence-designer
Use when the user asks to "design a welcome flow", "set up an abandoned-cart sequence", "build a light re-engagement branch inside a lifecycle flow", or "plan a cold-outbound sequence"; produces general lifecycle automation flows (welcome, cart, browse-abandon, post-purchase, in-flow re-engagement, B2B cold outbound)…
reactivation-specialist
Use when the user asks to "build a win-back campaign", "re-engage lapsed subscribers", "run a re-permission / re-consent sweep", or "sunset my dead list"; produces a closed-loop reactivation program — a lapsed-cohort definition, a staged offer ladder, a re-consent (re-permission) capture step, and a sunset-confirm /…
campaign-planner
Use when the user asks to "plan an influencer campaign", "build a campaign blueprint", "track or close a creator campaign", or "record a late campaign correction"; produces the plan and, when requested, a non-canonical evidence tracker with scoped identity, publication, reconciliation, close, and reopen receipts. Not…
product-feed-optimizer
Use when the user asks to "optimize my Shopping feed", "fix product disapprovals", "improve product titles/attributes", or "build feed-driven PMax asset groups"; audits and rewrites the Shopping/Performance Max product feed — title/description patterns, required and recommended attributes, GTIN/availability/price…
cold-outbound-sequencer
Use when the user asks to "build a B2B cold-outbound sequence", "design reply-triage branching", "plan a domain warmup / sending throttle", or "make my outbound CAN-SPAM / opt-in compliant"; produces a multi-step outbound sequence with reply-triage branches (positive / objection / referral / not-now / opt-out), a…