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 build-with-dhiraj/ai-workflow-framework-portability-kit --skill json-canvasgit clone --depth 1 https://github.com/build-with-dhiraj/ai-workflow-framework-portability-kitWrote 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/build-with-dhiraj/ai-workflow-framework-portability-kit/json-canvas)<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/json-canvas"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/json-canvas/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/build-with-dhiraj/ai-workflow-framework-portability-kit/json-canvas"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/json-canvas.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 | $0.00054 | $0.02225 |
| Opus 5.5 | $0.00022 | $0.00890 |
| Sonnet 5.5 | $0.00011 | $0.00445 |
| Haiku 4.5 | $0.00005 | $0.00222 |
Grade A, and why
json-canvas 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 1mo 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.
This is a copy
100% identical to json-canvas — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JSON Canvas Skill
File Structure
A canvas file (.canvas) contains two top-level arrays following the JSON Canvas Spec 1.0:
{
"nodes": [],
"edges": []
}
nodes(optional): Array of node objectsedges(optional): Array of edge objects connecting nodes
Common Workflows
1. Create a New Canvas
- Create a
.canvasfile with the base structure{"nodes": [], "edges": []} - Generate unique 16-character hex IDs for each node (e.g.,
"6f0ad84f44ce9c17") - Add nodes with required fields:
id,type,x,y,width,height - Add edges referencing valid node IDs via
fromNodeandtoNode - Validate: Parse the JSON to confirm it is valid. Verify all
fromNode/toNodevalues exist in the nodes array
2. Add a Node to an Existing Canvas
- Read and parse the existing
.canvasfile - Generate a unique ID that does not collide with existing node or edge IDs
- Choose position (
x,y) that avoids overlapping existing nodes (leave 50-100px spacing) - Append the new node object to the
nodesarray - Optionally add edges connecting the new node to existing nodes
- Validate: Confirm all IDs are unique and all edge references resolve to existing nodes
3. Connect Two Nodes
- Identify the source and target node IDs
- Generate a unique edge ID
- Set
fromNodeandtoNodeto the source and target IDs - Optionally set
fromSide/toSide(top, right, bottom, left) for anchor points - Optionally set
labelfor descriptive text on the edge - Append the edge to the
edgesarray - Validate: Confirm both
fromNodeandtoNodereference existing node IDs
4. Edit an Existing Canvas
- Read and parse the
.canvasfile as JSON - Locate the target node or edge by
id - Modify the desired attributes (text, position, color, etc.)
- Write the updated JSON back to the file
- Validate: Re-check all ID uniqueness and edge reference integrity after editing
What ships with it
1 file 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.
- 1mo ago First seen · 245 lines · 54 tokens per session scan A 97d1ae072895
json-canvas is a skill published in the GitHub repository build-with-dhiraj/ai-workflow-framework-portability-kit (5 stars, last pushed 21d ago), licensed MIT. It adds 54 tokens to every session and 2,225 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to json-canvas, differing in 0 lines, and is treated as a copy.
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