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-reportgit 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-report)<a href="https://agentmods.dev/skills/orkas-ai/orkas/seo-report"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-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/orkas-ai/orkas/seo-report"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-report.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 | $0.01366 |
| Opus 5 | $0.00001 | $0.00683 |
| Sonnet 5 | $0.00000 | $0.00273 |
| Haiku 4.5 | $0.00000 | $0.00137 |
Grade A, and why
seo-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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-report
Render an audit into the deliverable: a dashboard spec the chat can show inline, and a written action plan. Pure formatting — no network, no scoring (it trusts the audit, opportunity and probe inputs).
When to use
- The diagnose flow has a
seo-tech-auditresult and needs the user-facing report + dashboard. - The diagnose flow has
seo-opportunityand/orgeo-probe --op scoreoutput to include in the same one-run report. - Producing a monitoring snapshot's dashboard from a fresh audit.
When NOT to use
- Scoring or generating findings — that is
seo-tech-audit. - Acquiring page data — that is
seo-crawl.
Preconditions
On a continuation, supplied current-run evidence remains usable context. Finish the pending artifact from it, keeping unsupported findings Estimated, instead of restarting collection merely because the work spans turns.
- A
seo-tech-auditJSON object. Optionally the originatingseo-crawlJSON,seo-opportunityJSON, andgeo-probe --op scoreJSON for extra context. - Python 3.9+ (stdlib only).
How to call
For a bounded end-to-end diagnosis, first run seo-crawl --out so its compact
summary supplies representative links, then call this orchestrator once:
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" seo-report diagnose -- --crawl .orkas-seo-audit/crawl.json --out-dir .orkas-seo-audit [--sample-url <url> ...] [--include-cwv]
It runs root tech/content/schema/GEO/opportunity analysis, audits at most five
explicit sample URLs once each, writes multi-summary.json and report.json,
and returns the dashboard, action_plan_md, page matrix, and optional CWV
failure in one envelope. A failed sample is recorded and not retried. The
workspace-relative output directory rejects absolute and parent-traversal
paths. Use write_file for the returned action_plan_md.
For report-only assembly from existing inputs:
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" seo-report report -- --audit <audit.json> [--crawl <crawl.json>] [--opportunities <opportunities.json>] [--geo-probe <geo-probe.json>] [--plan <ACTION-PLAN.md>] [--out <dashboard.json>]
What ships with it
4 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 · 110 lines · 2 tokens per session scan A 35a30ccd00a1
seo-report 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 1,366 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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