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 image-design-reviewgit 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/image-design-review)<a href="https://agentmods.dev/skills/orkas-ai/orkas/image-design-review"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/image-design-review/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/image-design-review"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/image-design-review.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 | $0.01737 |
| Opus 5 | $0.00002 | $0.00869 |
| Sonnet 5 | $0.00001 | $0.00347 |
| Haiku 4.5 | $0.00000 | $0.00174 |
Grade A, and why
image-design-review 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Design Review
Read this skill only after a passing COMPOSE or HYBRID image_studio project.snapshot returns visual_evidence.attached:true. Never load it at task start, during routing, or in the same parallel batch as image-router. Never use it for a GENERATE or EDIT raster, including strict reproduction, semantic editing, explicit visual-QA wording, or multi-image consistency; the configured image service owns those guarantees. Inspect the attached complete full-color composition, not a textual description of it, a media URL, or the generic read_files grayscale preview of the same path. Failed deterministic inspection intentionally returns no visual attachment and must be repaired before this review begins.
Review rubric
Check, in order:
- Intent: the image communicates the manifest's
one_joband honors required subject, copy, references, and exclusions. Supplementary creative copy is allowed unless strict fidelity was requested. For strict, exact-only, or no-added-copy requests, treat any visible text outside the user's supplied copy as a blocker. - Canvas and references: first read
reference_intent.mode. For reproduce, compare every preserved attribute; for edit, verify every instruction while checking that protected/unaffected regions remain stable; for guide, ensure references influence only their declared role. Every planned region must remain visible in the intended reading order and no unrequested reference drift may appear. Review the exact candidate path returned by the generation/edit handoff. It must byte-for-byte match the plannedoutput_path; a missing or retyped path is a blocker, not a candidate to guess. - Composition: focal hierarchy, crop, scale, balance, negative space, edge tension, and thumbnail legibility. Read each required headline line by line. An automatic wrap that leaves a one-glyph orphan line is a
fix; widen the text box, reduce the type size, or use an intentional balanced break before passing. A decorative rule, stroke, or signature device that crosses, crowds, masks, or visually splits required copy is afix(or ablockerwhen the copy becomes unreadable), never a passing flourish. - Craft: lighting logic, color relationships, depth, material behavior, typography, alignment, and purposeful detail. Verify that English titles use sentence case or natural title case and body/supporting copy uses sentence case unless exact required copy or an external brand/source explicitly preserves different casing.
- Generation defects: anatomy, duplicated or fused objects, malformed hands/faces, unreadable pseudo-text, inconsistent perspective, and reference drift.
- Specificity: the signature device is visible and the result does not collapse into a generic template or undirected model aesthetic.
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 · 57 lines · 3 tokens per session scan A 0117f38f2da6
image-design-review 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 1,737 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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