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/ecomfe/tempad-dev/figma-design-to-codenpx skills add ecomfe/tempad-dev --skill figma-design-to-codegit clone --depth 1 https://github.com/ecomfe/tempad-devWhat 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 | $0.00093 | $0.03562 |
| Opus 5 | $0.00046 | $0.01781 |
| Sonnet 5 | $0.00019 | $0.00712 |
| Haiku 4.5 | $0.00009 | $0.00356 |
Grade A, and why
figma-design-to-code 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- figma-design-to-code — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TemPad Dev: Figma Design to Code
Use this skill to turn TemPad Dev design evidence into project-consistent UI code.
TemPad Dev MCP must be available and able to provide trustworthy design
evidence for the current selection or provided nodeId. If not, stop and tell
the user to enable or reconnect TemPad Dev MCP.
Within this skill, TemPad Dev MCP is the authoritative source of design evidence. Treat:
- project files and project instructions as implementation truth when available
- TemPad Dev output as design truth
- the user as the source of truth for missing product or implementation decisions
Do not infer project conventions before reading local evidence.
For concerns orthogonal to Figma-to-code translation, follow project
instruction files such as AGENTS.md and other project instructions instead of
defining new policy in this skill. If such a concern is unspecified there and
would materially change the implementation, ask the user or stop.
Evidence model
Use three evidence channels for different jobs:
- Project evidence:
AGENTS.mdor equivalent project instruction files, design-system docs, token/theme docs, component docs, existing primitives, nearby implementations, framework/styling config, asset rules, and project scripts - Design evidence:
tempad-dev:get_codefirst for markup, styles, tokens, assets, warnings, and codegen facts;tempad-dev:get_structureonly for hierarchy, geometry, overlap, and retry targeting - User input: missing behavioral intent, responsive intent, target file, acceptable tradeoffs, asset or dependency decisions, or other product or implementation decisions that cannot be recovered from project or design evidence
What TemPad Dev can and cannot prove
TemPad Dev can prove:
- the visible structure of the current selection or a provided
nodeId - explicit layout, spacing, typography, color, radius, borders, shadows, gradients, masks, filters, compositing, and other rendered visual details
- token references and values when present
- exported assets and whether an SVG may safely adopt one contextual color
channel via
themeable - codegen facts such as actual output language,
cssUnit,scale, androotFontSize
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.
- 3d ago First seen · 393 lines · 93 tokens per session scan A 8059da321389
figma-design-to-code is a skill published in the GitHub repository ecomfe/tempad-dev (495 stars, last pushed 5d ago), licensed MIT. It adds 93 tokens to every session and 3,562 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…