Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/southleft/figma-console-mcp-skillsnpx agentmods add skills/southleft/figma-console-mcp-skills/figma-blame-nodeWrote 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/southleft/figma-console-mcp-skills/figma-blame-node)<a href="https://agentmods.dev/skills/southleft/figma-console-mcp-skills/figma-blame-node"><img src="https://agentmods.dev/badge/skills/southleft/figma-console-mcp-skills/figma-blame-node/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/southleft/figma-console-mcp-skills/figma-blame-node"><img src="https://agentmods.dev/badge/skills/southleft/figma-console-mcp-skills/figma-blame-node.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 3 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 13 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 13 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00176 | $0.01351 |
| Opus 5 | $0.00088 | $0.00675 |
| Sonnet 5 | $0.00035 | $0.00270 |
| Haiku 4.5 | $0.00018 | $0.00135 |
Grade A, and why
figma-blame-node 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
figma-blame-node — binary-search which version introduced a change
Like git blame, but for Figma. Given a node and a target (a componentPropertyDefinitions key or
a descendant child node id), this localizes the version that first introduced the target and
returns that version's label, author handle, and timestamp.
Setup — terminal + token required. This skill runs shell commands, so it works in Claude Code (including the "Code" tab inside Claude Desktop), Cursor, Codex, or Gemini CLI — it does not run in plain Claude Desktop or claude.ai chat (no shell). The Figma connector's OAuth login does not authorize these REST calls, so you must supply your own Figma personal access token: in Figma go to Settings → Security → Personal access tokens, generate one with scope File content: read (plus File versions: read), then set it in your shell:
export FIGMA_TOKEN="figd_…". The script reads it from the environment at runtime — never put the token in a skill file.
Why binary search
A naive walk would fetch the node at every version — N API calls for N versions. Existence of a
target is monotonic (added once, then present in every newer version up to HEAD), so we binary
search: probe the midpoint, check whether the target exists there, then narrow to the older or newer
half. That's ~log2(N) calls — e.g. ~8 probes across 200 versions instead of 200. This is the
rate-limit-friendly approach: Figma REST is throttled per token, and old snapshots are immutable, so
fewer probes is strictly better.
Setup & skill boundaries
- All requests use
X-Figma-Token: $FIGMA_TOKENagainsthttps://api.figma.com.
Derive the file key
FILE_KEY=$(echo "$FILE_URL" | sed -E 's#.*/(design|file)/([A-Za-z0-9]+).*#\2#')
Workflow
- Identify the node and the target.
node_idis typically a COMPONENT_SET. The target is exactly one of:--property '<key>'— acomponentPropertyDefinitionskey likeDisabled#1:2, or--child '<node_id>'— a descendant node id that should appear undernode_id.
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.
- 11d ago First seen · 87 lines · 176 tokens per session scan A d625694b4383
figma-blame-node is a skill published in the GitHub repository southleft/figma-console-mcp-skills (80 stars, last pushed 25d ago), licensed MIT. It adds 176 tokens to every session and 1,351 once invoked, about $0.0009 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
design-to-code
Use this skill when translating UI/UX designs into production-ready frontend code. Handles design source ingestion (Figma, Sketch, Adobe XD, screenshots, design specs), design token extraction, component hierarchy mapping, responsive breakpoint strategy, accessibility-first implementation (WCAG 2.1 AA minimum)…
design-md
Author/validate/export Google's DESIGN.md token spec files.
system-pitch
Write a design system investment pitch with a business case and ROI framing. Trigger when someone says: pitch the design system, make the case for the system, sell this to leadership, justify the investment, business case for design systems, why should we invest in a design system, or anything about building an…
token-audit
Audit a design system's token definitions for naming violations, missing semantic tiers, and structural debt. This audits how tokens are defined and organised, NOT how they are consumed in code. Trigger when someone says: audit my tokens, token naming review, are my tokens consistent, token health check, review my…
ai-component-description
Generate AI-optimised text descriptions for components, formatted for Figma's MCP server and LLM consumption. This produces prose descriptions in a six-section format (purpose, props, anti-patterns, composition, accessibility, examples), NOT JSON schemas or structured data files. Trigger when someone says: write…
context-engine-builder
Generate a context engine — seven structured blueprint files (UX, UI, content, accessibility, ethical, technical, business intelligence) that encode everything an AI agent needs to work with a design system. This produces YAML infrastructure in .ai/context-engine/, NOT a health score or quality assessment. Trigger…