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 it235/multica-best-practices --skill multica-platform-figmagit clone --depth 1 https://github.com/it235/multica-best-practicesWrote 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/it235/multica-best-practices/multica-platform-figma)<a href="https://agentmods.dev/skills/it235/multica-best-practices/multica-platform-figma"><img src="https://agentmods.dev/badge/skills/it235/multica-best-practices/multica-platform-figma/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/it235/multica-best-practices/multica-platform-figma"><img src="https://agentmods.dev/badge/skills/it235/multica-best-practices/multica-platform-figma.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 | $0.00037 | $0.00246 |
| Opus 5.5 | $0.00015 | $0.00098 |
| Sonnet 5.5 | $0.00007 | $0.00049 |
| Haiku 4.5 | $0.00004 | $0.00025 |
Grade A, and why
multica-platform-figma 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.
What it actually says
Figma Platform
Responsibility
Integrate Figma: read file metadata / design summaries so downstream skills (designer, tester) can derive UI test points and design traceability. All Figma credentials and the Figma API are only looked up here.
Capabilities
fetch_file.py: pull a Figma file's nodes/metadata by file key.- Summarize design states (normal/empty/error/loading) for test-point generation.
Usage
- Designer: consume design links produced here.
- Tester (T1): derive UI checkpoints from the design summary (see
multica-test-t1-design→web-ui-checkpoints.md).
Credentials
FIGMA_TOKENvia environment variable or Secret; seescripts/fetch_file.py --help.- Never hardcode tokens in skill content.
What ships with it
3 files 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 Changed · -35 lines · -8 tokens per session 09a4d9b0a932
- 1mo ago First seen · 63 lines · 45 tokens per session scan A e0e170bc9bab
multica-platform-figma is a skill published in the GitHub repository it235/multica-best-practices (212 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 246 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-07.
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