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 seo-opportunitygit 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/seo-opportunity)<a href="https://agentmods.dev/skills/orkas-ai/orkas/seo-opportunity"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-opportunity/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/seo-opportunity"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-opportunity.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 | $0.00003 | $0.01096 |
| Opus 5 | $0.00002 | $0.00548 |
| Sonnet 5 | $0.00001 | $0.00219 |
| Haiku 4.5 | $0.00000 | $0.00110 |
Grade A, and why
seo-opportunity 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-opportunity
For product-focused strategy, prefer observed use-case, pricing, comparison, and trust/docs pages. Name missing page types as coverage gaps and map recommendations to owned pages, first-party proof, answer blocks, and one cannibalization owner per overlapping query cluster.
Build a one-diagnosis keyword/GEO opportunity pool. This skill is deterministic and stdlib-only: it does not fetch data, call models, or persist anything.
Connector acquisition invariant: naming connector operations is not enough. Discover each connected console with list_connector_tools, then invoke its selected operations through the core call_connector_tool; for GSC the order is list_sites before query_search_analytics.
Ownership evidence invariant: a verified Search Console property is not evidence that its root URL owns a query. When query evidence lacks a page dimension, keep the owner page unconfirmed, request query+page rows, and defer owner-page edits until that row or crawl evidence identifies the target. Never convert a property-level query row into a homepage claim.
When to use
- After
seo-crawland any available Search Console / Bing Webmaster query exports. - After
geo-probe --op scorewhen the diagnose flow wants GEO gaps folded into the action plan. - When the user wants "what should I do first?" rather than only technical findings.
When NOT to use
- Historical decay/trend analysis. This skill has no persistence and should not claim trends.
- Fetching GSC/Bing data. The agent/connector does that before calling this skill.
- Writing content or editing files.
Preconditions
- Python 3.9+ (stdlib only).
- At least one
seo-crawlJSON. GSC/Bing/GEO inputs are optional.
Connector evidence acquisition
Connector availability is closed-world: consume, reconcile, and name every runtime-listed console, never omit a second console, and never probe one from memory. Without returned console evidence, rankings and traffic remain Estimated.
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.
- 12d ago First seen · 85 lines · 3 tokens per session scan A a4564985c8d0
seo-opportunity is a skill published in the GitHub repository Orkas-AI/Orkas (1,885 stars, last pushed yesterday), licensed MIT. It adds 3 tokens to every session and 1,096 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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