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 sfc-gh-abannerjee/SnowGram --skill connected-uigit clone --depth 1 https://github.com/sfc-gh-abannerjee/SnowGramWrote 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/sfc-gh-abannerjee/snowgram/connected-ui)<a href="https://agentmods.dev/skills/sfc-gh-abannerjee/snowgram/connected-ui"><img src="https://agentmods.dev/badge/skills/sfc-gh-abannerjee/snowgram/connected-ui/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/sfc-gh-abannerjee/snowgram/connected-ui"><img src="https://agentmods.dev/badge/skills/sfc-gh-abannerjee/snowgram/connected-ui.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 | $0.00040 | $0.01144 |
| Opus 5.5 | $0.00016 | $0.00458 |
| Sonnet 5.5 | $0.00008 | $0.00229 |
| Haiku 4.5 | $0.00004 | $0.00114 |
Grade A, and why
snowflake-architecture-diagram-connected-ui scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /dev/null -w "%{http_code}" --max-time 1 http://localhost:8082/health || true How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connected-UI mode
Defers to the live SnowGram Next.js frontend at localhost:3002 (backed by the FastAPI service at localhost:8082) for the full ReactFlow + ELK rendering experience and multi-tab conversational refinement.
This mode does NOT spawn the lightweight viewer. The user gets pixel-identical SnowGram output, but at the cost of two running processes.
Prerequisites
- Connected-CLI prerequisites (connection + agent reachable)
- SnowGram backend running at
http://localhost:8082 - SnowGram frontend running at
http://localhost:3002 frontend/.env.localpopulated with a validSNOWFLAKE_PATfor the active accountbackend/.envpopulated with connection details
Workflow
Step 1: Probe both servers
curl -s -o /dev/null -w "%{http_code}" --max-time 1 http://localhost:8082/health || true
curl -s -o /dev/null -w "%{http_code}" --max-time 1 http://localhost:3002/ || true
| Backend | Frontend | Action |
|---|---|---|
| 200 | 200 | Continue to Step 2 |
| 200 | down | Print frontend start command, stop |
| down | 200 | Print backend start command, stop |
| down | down | Print both start commands, stop |
Do NOT auto-start servers. They may need credentials, port adjustments, or other manual setup.
Start commands to print:
# Backend (terminal 1)
cd <repo>/backend
source venv/bin/activate
python -m api.main
# Frontend (terminal 2)
cd <repo>/frontend
npm run dev
⚠️ STOP: tell the user which servers are down and what to run, then exit. They will resume the skill once both are up.
Step 2: Optional pre-seed via agent
If the user provided a prompt, invoke the agent once via CLI to pre-seed the canvas before opening the browser:
cortex agents run SNOWGRAM_DB.AGENTS.SNOWGRAM_AGENT "<user's prompt>"
Capture the response and POST it to the running backend so the frontend has a default tab populated:
curl -X POST http://localhost:8082/api/diagram/seed \
-H "Content-Type: application/json" \
-d '{"mermaid": "<extracted>", "title": "<short>"}'
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.
- 2mo ago First seen · 125 lines · 40 tokens per session scan A 9422bf3adb31
snowflake-architecture-diagram-connected-ui is a skill published in the GitHub repository sfc-gh-abannerjee/SnowGram (2 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,144 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
snowflake-architecture-diagram-connected-ui compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| snowflake-architecture-diagram-connected-uisfc-gh-abannerjee/SnowGram | Skill | 2 | 1mo ago | MIT | A | 40 | Claude Code, Codex |
| webgl-holographic-foilnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 41 | Claude Code, Codex |
| html-ppt-hermes-cyber-terminalnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 53 | Claude Code, Codex |
| html-ppt-taste-brutalistnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 78 | Claude Code, Codex |
| visual-ralphYeachan-Heo/oh-my-codex | Skill | 34k | 3d ago | MIT | A | 52 | Codex |
| glance-canonical-layoutsandroid/skills | Skill | 10k | yesterday | Apache-2.0 | A | 56 | Claude Code |
| accessibilitymicrosoft/hve-core | Skill | 1.6k | yesterday | MIT | A | 47 | Claude Code |