Borrowing it
Nothing to install: this file belongs to LedgerHQ/ledger-live. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/LedgerHQ/ledger-live/develop/.agents/skills/analytics/SKILL.mdgit clone --depth 1 https://github.com/LedgerHQ/ledger-liveWrote 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/ledgerhq/ledger-live/analytics)<a href="https://agentmods.dev/skills/ledgerhq/ledger-live/analytics"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/analytics/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/ledgerhq/ledger-live/analytics"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/analytics.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 | $0.00028 | $0.00334 |
| Opus 5.5 | $0.00011 | $0.00134 |
| Sonnet 5.5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
analytics 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.
What it actually says
Product analytics
The API is @shared/analytics. React adapters are @shared/analytics-react.
- Import
trackandtrackPagefrom@shared/analyticsandTrackandTrackScreenfrom@shared/analytics-react.TrackScreenis one component on both platforms: web tracks when its props change, native when the screen gains focus. - Do not re-export
track,trackPage,TrackorTrackScreenfrom app modules. Appsegment.tsfiles only wire the host. - Register the Segment client, consent,
identify, extra props, and props filters in app (currently/apps/**/segment.ts). - Flow packages may keep an injected
trackhelper so tests can pass a fake. They must not import an app barrel. - In tests, mock
@shared/analytics(and@shared/analytics-reactwhen the component is under test). - Do not put PII in event payloads. See detect-data-leaks and client-ids.
Portfolio charts (@ledgerhq/wallet-analytics) are a different package. Consent models stay in their own READMEs; apps only wire them into setEnabledFn and updateIdentify.
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 Changed 917f945111b4
- 26d ago Changed 04b073763f75
- 29d ago First seen · 18 lines · 28 tokens per session scan A d5caddddf9f2
analytics is a skill published in the GitHub repository LedgerHQ/ledger-live (624 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 334 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 2026-09-30.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…