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 e8868f762c1dgit 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/e8868f762c1d)<a href="https://agentmods.dev/skills/orkas-ai/orkas/e8868f762c1d"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/e8868f762c1d/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/e8868f762c1d"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/e8868f762c1d.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 | $0.00004 | $0.00322 |
| Opus 5.5 | $0.00002 | $0.00129 |
| Sonnet 5.5 | $0.00001 | $0.00064 |
| Haiku 4.5 | $0.00000 | $0.00032 |
Grade A, and why
ecommerce-review-analysis 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 15d 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
Ecommerce Review Analysis
- Identify the corpus and intended decision. Read data preparation to map fields, deduplicate and preserve platform/product/variant/time boundaries.
- Use VOC taxonomy to label purchase scenarios, positive drivers and complaints. Retain a link from each theme to actual anonymized source records.
- Use root causes and actions to separate symptoms from hypotheses and prioritize corrective work.
- Deliver the evidence-led summary at the requested depth. Report what the sample supports, what it excludes and the next useful validation.
Supplied CSV, spreadsheet, JSON or document exports require no external data provider. Public reputation samples are supplementary, not complete seller analytics. This Skill ships no review scraper. Do not treat rating, text sentiment, verified purchase or fraud suspicion as interchangeable facts.
What ships with it
5 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.
- 15d ago Changed · -1 lines 3d130c8974d1
- 24d ago First seen · 16 lines · 4 tokens per session scan A 19e232cf38a5
ecommerce-review-analysis is a skill published in the GitHub repository Orkas-AI/Orkas (2,192 stars, last pushed today), licensed MIT. It adds 4 tokens to every session and 322 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-23.
Other skills, from other repositories
cross-border-customer-service-brief
Cluster refund, return, complaint, and bad-review notes into a daily support brief with response guidance and escalation hints.
cross-border-listing-image-layout-audit
Audit listing image and layout notes — first-impression hero, info hierarchy, lifestyle vs studio, copy density, trust signals, compliance — into a follow-up checklist.
cross-border-price-match-review
Cluster competitor price, coupon, shipping, and bundle observations into a price-gap review with explicit human-approval guidance.
cross-border-top-category-watch
Cluster category Top 10 movement, seller shifts, pricing changes, and creative updates into a daily watch board.
summarize-shop-performance
Cluster cross-border store-health, refund, fulfillment, ad-spend, and listing-quality notes into a daily action board.
tutti-agent-workspace-app
Build or evolve a complex agent-enabled Tutti workspace app repository. Use for Tutti apps with web/server/shared monorepos, @tutti-os/agent-acp-kit local agent runtimes, kit-owned TUTTICLI agent/composer discovery, dynamic agent catalogs, run-scoped MCP tool gateways, app-owned package builders, web-first debugging…