Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.
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 Orkas-AI/Orkas --skill geo-scoregit clone --depth 1 https://github.com/Orkas-AI/OrkasWrote 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/orkas-ai/orkas/geo-score)<a href="https://agentmods.dev/skills/orkas-ai/orkas/geo-score"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/geo-score/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/orkas-ai/orkas/geo-score"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/geo-score.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00002 | $0.00665 |
| Opus 5 | $0.00001 | $0.00332 |
| Sonnet 5 | $0.00000 | $0.00133 |
| Haiku 4.5 | $0.00000 | $0.00067 |
Grade A, and why
geo-score scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
geo-score
Score how citable/ready a page is for AI answer engines, from crawl facts. Pure analysis — no network, no model calls. Deterministic so it is drift-comparable.
When to use
- The diagnose flow wants a GEO score + GEO recommendations alongside the SEO audit.
- A geo-only pass focused on AI-citation readiness.
When NOT to use
- Measuring whether models actually cite the site (real visibility) — that needs probing models, not on-page scoring (see the probe step the agent runs).
- Technical SEO health — that is
seo-tech-audit.
Preconditions
- A
seo-crawlJSON (uses first_paragraph, headings, images/alt, structured_data + sameAs, indexability, https, word_count, and site robots.txt). Python 3.9+ stdlib only.
How to call
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" geo-score geo_score -- --input <crawl.json> [--out <geo.json>]
Expected output
{ "ok": true, "data": {
"geo_score": 92,
"geo_dimensions": { "citability": 100, "structure": 100, "multimodal": 100, "authority": 100, "technical": 100 },
"entity_status": "recognized",
"geo_recommendations": [ { "dimension": "geo:authority", "title": "...", "evidence": "...",
"recommendation": "...", "leading_indicator": "...",
"failure_criterion": "...", "data_tier": "Estimated" } ],
"meta": { "url": "...", "entity_status": "recognized" } } }
Pass to seo-report --geo <geo.json> — it shows the GEO score + dimension chart and a GEO section in the action plan, kept separate from the SEO health score. Failure: {"ok": false, "error": "..."}, non-zero exit.
Scoring
Weighted: Citability 25% · Structure 20% · Multimodal 15% · Authority&Brand 20% · Technical-access 20%. Signals: answer-first opening, heading hierarchy, image alt coverage, Organization JSON-LD + sameAs (entity resolution), outbound citations, indexability, HTTPS, raw-HTML content, AI-crawler reachability in robots.txt.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 50 lines · 2 tokens per session scan A 79096a5fa82a
geo-score is a skill published in the GitHub repository Orkas-AI/Orkas (1,885 stars, last pushed today), licensed MIT. It adds 2 tokens to every session and 665 once invoked, about $0.0000 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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