modellix-agent-canvas: Skill for Claude Code

.agents/skills/modellix-agent-canvas-image-edit/SKILL.md

modellix-agent-canvas-image-edit is a skill for Claude Code from Modellix/modellix-agent-canvas. It costs 44 tokens per session (507 once invoked), scanned A, original, MIT.

A workflow for editing images stored in Modellix Agent Canvas, including composites made from images and annotations. It preserves the selected image order and supports transparent or high-resolution output.

In plain words
What is it for?
Editing one or more Canvas images, combining references, applying annotated changes, and placing the result beside the original image.
Why use it?
It provides a controlled process for sending the right Canvas images to an editing task and recovering from problems.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: installed under .agents/ (shared by several agents).

This is Modellix/modellix-agent-canvas's own configuration. It tells Claude Code how to work on modellix-agent-canvas itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything modellix-agent-canvas configures →

Part of the modellix-agent-canvas plugin — 3 skills, 2 MCP servers shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to Modellix/modellix-agent-canvas. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Modellix/modellix-agent-canvas/main/.agents/skills/modellix-agent-canvas-image-edit/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Modellix/modellix-agent-canvas

Made for: Claude Code.

Or install modellix-agent-canvas, the plugin that ships this one along with the rest of its 3 skills, 2 MCP servers.

Wrote 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.

agentmods badge for modellix-agent-canvas-image-edit

README.md
[![agentmods](https://agentmods.dev/badge/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit/github.svg)](https://agentmods.dev/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit)
Your own site
<a href="https://agentmods.dev/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit"><img src="https://agentmods.dev/badge/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit/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.

agentmods 80×15 button for modellix-agent-canvas-image-edit

Your own site · 80×15
<a href="https://agentmods.dev/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit"><img src="https://agentmods.dev/badge/skills/modellix/modellix-agent-canvas/modellix-agent-canvas-image-edit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 507 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.00507
Opus 5 $0.00022 $0.00253
Sonnet 5 $0.00009 $0.00101
Haiku 4.5 $0.00004 $0.00051

Measured 10d ago against content hash 825f3a1900ec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

modellix-agent-canvas-image-edit 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 10d 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.

.agents/skills/modellix-agent-canvas-image-edit/SKILL.md · 21 lines

What it actually says

Edit images in Modellix Agent Canvas

Use the Modellix Canvas MCP task tools. Never pass arbitrary local paths or remote image URLs, and never select a provider model slug yourself.

  1. Call get_canvas_context and obtain project-local image business object IDs. Preserve user order, make the first image the explicit primary reference, remove content duplicates while keeping the first occurrence, and use at most 10 images.
  2. For annotation editing, flatten the selected source image, arrows, shapes, strokes, and text with safety padding into a project asset. Keep the source image and every annotation unchanged.
  3. Call get_modellix_canvas_status with refresh: true; if required, open Canvas and let the user configure the Key in its embedded isolated credential field. Use start_modellix_api_key_setup only when the host cannot display or open Canvas.
  4. Call prepare_modellix_image_task with mode: edit, ordered sourceObjectIds and/or project sourceAssetIds, a non-empty prompt, requested size/fit/quality/background/fidelity, count from 1 through 4, active pageId, and the primary image as targetObjectId.
  5. Prepare is non-paying. Show the actual model, route reason, primary/reference count, effective specification, every warning, output count, unit/total estimate, currency, and expiry.
  6. After explicit confirmation, submit the unchanged intent with a fresh operationId, returned routeFingerprint, and confirmedPaidSubmission: true.
  7. Poll and immediately finalize successful tasks. Report partial failures independently. Never resubmit an unknown outcome; recover it from list_modellix_canvas_tasks.
  8. Finalization must preserve, not move, hide, delete, or overwrite source images and annotations. Results go to the right in a stable grid unless the confirmed target is an AI image holder.

For ordinary single-image editing, the default route is GPT Image 2 Edit. Transparent, strict-fidelity, and standard multi-reference requests use a compatible GPT Image 1.5 Edit route; multi-reference special-ratio or 2K/4K requests can route to Nano Banana Pro Edit. Treat the prepare response as authoritative.

Changes

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.

  1. 10d ago First seen · 21 lines · 44 tokens per session scan A 825f3a1900ec

Subscribe to this mod's changes

modellix-agent-canvas-image-edit is a skill published in the GitHub repository Modellix/modellix-agent-canvas (0 stars, last pushed 29d ago), licensed MIT. It adds 44 tokens to every session and 507 once invoked, about $0.0002 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 2026-08-31.

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