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 agentmods add skills/pmdevsolutions/aurelius/canva-intakenpx skills add PMDevSolutions/Aurelius --skill canva-intakegit clone --depth 1 https://github.com/PMDevSolutions/AureliusWrote 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/pmdevsolutions/aurelius/canva-intake)<a href="https://agentmods.dev/skills/pmdevsolutions/aurelius/canva-intake"><img src="https://agentmods.dev/badge/skills/pmdevsolutions/aurelius/canva-intake.svg" alt="Measured on agentmods" 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 | $0.00066 | $0.02952 |
| Opus 5 | $0.00033 | $0.01476 |
| Sonnet 5 | $0.00013 | $0.00590 |
| Haiku 4.5 | $0.00007 | $0.00295 |
Grade A, and why
canva-intake 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 yesterday.
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 — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Canva Intake — Structured Discovery
Purpose
Gather everything needed to build a React app from a Canva design in a single structured pass. Uses the Canva AI Connector MCP to export screenshots, Claude's vision capabilities to analyze design structure, asks the user only what it must, and outputs a machine-readable build-spec.json that downstream skills consume without re-asking questions.
When to Use
- First phase of
/build-from-canvapipeline - Any time a user provides a Canva URL and wants to build from it
- When you need to understand a Canva design's structure before generating code
Inputs
- Required: Canva design URL (e.g.,
https://www.canva.com/design/DAGxyz.../...) - Optional: Existing project directory to integrate into
Process
Step 1: Auto-Discovery (No User Input)
Extract from Canva via MCP:
Use the Canva AI Connector MCP to interact with the design:
1. Search/identify the design from the URL
→ Design name, dimensions, page count
2. Export full-page screenshots (PNG, 2x scale)
→ One screenshot per page at high resolution
3. If multi-page: export each page separately
→ Individual page screenshots for detailed analysis
Vision analysis of screenshots:
Feed each exported screenshot to Claude for structural analysis:
1. Page structure:
- Identify distinct sections (hero, navigation, features, footer, etc.)
- Detect layout patterns (grid, flex, sidebar, stacked)
- Note responsive hints (if multiple artboards exist)
2. Component candidates:
- Buttons (variants: primary, secondary, ghost, etc.)
- Cards, inputs, modals, navbars, footers
- Repeated patterns that suggest reusable components
3. Visual hierarchy:
- Heading levels (H1, H2, H3) from size/weight
- Primary vs secondary actions
- Content grouping and spacing patterns
4. Text content:
- All visible text strings (headings, body, labels, CTAs)
- Placeholder text vs real content
Simultaneously scan the local project (identical to figma-intake):
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.
- yesterday First seen · 310 lines · 0 tokens per session scan A 17b639bf963a
canva-intake is a skill published in the GitHub repository PMDevSolutions/Aurelius (8 stars, last pushed 21d ago), licensed MIT. It adds 66 tokens to every session and 2,952 once invoked, about $0.0003 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 2026-09-04.
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