Agent skill

Canvasight Imagegen

by Niall-Young in Niall-Young/Canvasight

Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node.

MITAuto-check passedMedia & Creative

Install Canvasight Imagegen

skills CLI
$ npx skills add Niall-Young/Canvasight --skill canvasight-imagegen -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Niall-Young/Canvasight canvasight-imagegen --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Niall-Young/Canvasight.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/canvasight/skills/canvasight-imagegen .claude/skills/canvasight-imagegen && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
canvasight-imagegen
GitHub stars
213
Token cost
~1.1k tokens
SKILL.md length
560 words
Files
2
Skills in repo
8
Repo updated
First seen
Licence
MIT

At a glance

Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node.

  • Works in 6 steps: Read the active task's exact… → Reuse a Canvasight native widget only… → Call get_canvasight_graph_context with… → …
  • The user invokes @Canvasight
  • SKILL.md covers Workflow and Boundaries
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Canvasight Imagegen is an agent skill from Niall-Young/Canvasight. Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node. Use when the user invokes @Canvasight or otherwise asks to generate, create, draw, or render a new image directly into Canvasight. Do not use for editing an existing Canvasight Asset in place.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Media & Creative, covering Image generation. The repository describes itself as: 用于梳理任务然后交付给 AI 工具的 plugin 插件. The licence is MIT.

When your agent uses it

  • The user invokes @Canvasight
  • Otherwise asks to generate
  • Render a new image directly into Canvasight
  • Editing an existing Canvasight Asset in place

Example prompts

  • “/canvasight-imagegen”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Read the active task's exact CODEX_THREAD_ID.
  2. Reuse a Canvasight native widget only when this task already has verified fullscreen ready evidence. Otherwise follow canvasight-open…
  3. Call get_canvasight_graph_context with the same threadId. Preserve its projectPath, contextId, documentRevision, and active Page identity…
  4. Invoke the system $imagegen Skill. Use its built-in tool path by default, one call per requested final image or variant. Follow its…
  5. Keep only outputs that pass imagegen inspection. Call add_canvasight_generated_images with
  6. Treat written, merged, and conflict-copy as successful imports. Report the target Page, created node count, managed project-relative…

What it can do on your machine

Read from SKILL.md and the folder at commit f47e0bf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Canvasight Imagegen loads about 1.1k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 560 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Niall-Young/Canvasight at commit f47e0bf, republished under its MIT licence (© Niall-Young). 560 words, ~1,089 tokens.

Download SKILL.mdSave it as .claude/skills/canvasight-imagegen/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
canvasight-imagegen
description
Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node. Use when the user invokes @Canvasight or otherwise asks to generate, create, draw, or render a new image directly into Canvasight. Do not use for editing an existing Canvasight Asset in place.

Canvasight Image Generation

Generate with the system $imagegen Skill, then import the accepted bitmap outputs through Canvasight's atomic generated-image tool. Never hand-edit .scatter, pass an unmanaged path to write_canvasight_graph, or substitute browser automation.

Workflow

  1. Read the active task's exact CODEX_THREAD_ID.
  2. Reuse a Canvasight native widget only when this task already has verified fullscreen ready evidence. Otherwise follow canvasight-open: call open_canvasight with that threadId, preserve its sessionId and openAttemptId, then call await_canvasight_widget_ready. Stop before generation unless the result is verified status: "ready" with React, project hydration, rendered canvas, and visible non-zero canvas evidence.
  3. Call get_canvasight_graph_context with the same threadId. Preserve its projectPath, contextId, documentRevision, and active Page identity before starting image generation. Later Page switches must not retarget the import.
  4. Invoke the system $imagegen Skill. Use its built-in tool path by default, one call per requested final image or variant. Follow its transparency, inspection, retry, and CLI-consent rules exactly.
  5. Keep only outputs that pass imagegen inspection. Call add_canvasight_generated_images with:
    • the exact threadId and captured projectPath;
    • the captured contextId and documentRevision as expectedRevision;
    • one stable unique clientMutationId for this exact batch, reused only for retries;
    • one { "path", "title"? } entry per final image, in the requested display order.
  6. Treat written, merged, and conflict-copy as successful imports. Report the target Page, created node count, managed project-relative paths, final prompt set, and whether imagegen used the built-in or user-approved CLI path.
Product-design option flow

When the request is to explore a product or UI design before frontend implementation:

  1. Resolve the target surface, intended user, outcome, viewport, and hard constraints before generation.
  2. Unless the user specifies another count, generate exactly three independent UI images. Each image is one distinct direction with a meaningfully different hierarchy, layout, or interaction model; never combine multiple directions into one image.
  3. Import all accepted options as separate Asset Nodes in their visible result order, then stop so the user can connect the preferred image into the ordinary canvas flow. Do not choose a direction or start implementation on the user's behalf.
  4. Run continues to start only from executable Task or Group surfaces. For this option flow, run the ordinary Task flow: connected image Assets travel with that Task exactly like node attachments did, while generated images outside its reachable flow are unrelated. An Asset never runs independently, and no separate selection marker or persisted role is needed.
  5. If the project exposes a matching product-design or image-to-code Skill, it may be named visibly in the downstream Task body. Do not persist a hidden Skill assignment or assume that an unavailable external Skill is installed.
Show full SKILL.md (127 more words)Show less

Boundaries

  • This Skill creates new PNG, JPEG, or WebP Asset Nodes only. Do not use it to mutate or replace an existing Canvasight Asset.
  • Import at most 16 final images per tool call. For a larger explicit request, use successive batches without dropping results.
  • Do not generate anything when native Canvasight opening or ready verification fails; the requested result could not be delivered to the canvas.
  • If imagegen fails, do not create a placeholder node. If import fails, keep the generated source and report the actionable Canvasight error.
  • On context_expired or context_revision_mismatch, do not guess a different Page. Explain that the captured Page binding expired and ask the user to repeat the image request.
  • Never expose daemon URLs, tokens, or managed absolute paths in the user-facing result.

© Niall-Young, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/canvasight/skills/canvasight-imagegen of Niall-Young/Canvasight.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit f47e0bf

Compare with similar skills

Canvasight Imagegen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Canvasight Imagegen compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Canvasight Imagegen this skillNiall-Young/Canvasight213—~1.1kAutomated safety check: PassMIT
AI Image Generation and Editingzhayujie/CowAgent47k—~1.3kAutomated safety check: PassMIT
Structured Image Generationbytedance/deer-flow84k4 repos~2.9kAutomated safety check: PassMIT
Canghe Comicfreestylefly/canghe-skills4618 repos~3.2kAutomated safety check: PassNone
Generate Imageynulihao/AgentSkillOS61810 repos~1.7kAutomated safety check: NotesNone
GPT Image Generation CLIwuyoscar/GPT-Image2-Skill5.7k—~2.5kAutomated safety check: NotesMIT

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Questions about Canvasight Imagegen

What does Canvasight Imagegen do?

Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node. Canvasight Imagegen is an agent skill from Niall-Young/Canvasight. Generate new raster images with Codex imagegen and add every final result to the active Canvasight Page as a managed Asset Node.

When should I use Canvasight Imagegen?

Canvasight Imagegen fits situations like: the user invokes @Canvasight; otherwise asks to generate; render a new image directly into Canvasight; editing an existing Canvasight Asset in place.

How do I install Canvasight Imagegen in Claude Code?

Run `npx skills add Niall-Young/Canvasight --skill canvasight-imagegen -a claude-code`. Or copy the skill folder (plugins/canvasight/skills/canvasight-imagegen in Niall-Young/Canvasight) into .claude/skills/canvasight-imagegen in your project. Claude Code loads it when a task matches its description.

How do I install Canvasight Imagegen in Codex?

Run `npx skills add Niall-Young/Canvasight --skill canvasight-imagegen -a codex`. Or copy the skill folder (plugins/canvasight/skills/canvasight-imagegen in Niall-Young/Canvasight) into .agents/skills/canvasight-imagegen in your project. Codex loads it when a task matches its description.

Can I use Canvasight Imagegen in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Niall-Young/Canvasight --skill canvasight-imagegen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/canvasight-imagegen, .gemini/skills/canvasight-imagegen, .github/skills/canvasight-imagegen and .opencode/skills/canvasight-imagegen in your project.

What does Canvasight Imagegen need to run?

SKILL.md names no scripts, command-line tools or credentials: Canvasight Imagegen is instructions for the agent only.

Does Canvasight Imagegen access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Canvasight Imagegen safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Canvasight Imagegen use?

Canvasight Imagegen is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Canvasight Imagegen use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Canvasight Imagegen?

Skills that share tags, products or a category with Canvasight Imagegen: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Structured Image Generation (bytedance/deer-flow, 84k stars), Canghe Comic (freestylefly/canghe-skills, 461 stars) and Generate Image (ynulihao/AgentSkillOS, 618 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Canvasight Imagegen?

Niall-Young (a GitHub user) maintains it in Niall-Young/Canvasight, which has 213 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on September 24, 2026.

Source: Niall-Young/Canvasight on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.