Agent skills for Claude Desktop

Generates a current RFC 6238 TOTP two-factor code from a shared secret the user already holds, via a bundled zero-dependency script that…

Friendly onboarding tour of Claude Code capabilities for users asking what it can do.

Automatically trace Claude Code conversations to Braintrust for observability.

Parses local CLI transcripts and accurately attributes work packages and commits to specific AI sessions.

When the user wants to implement shipment tracking, product traceability, or supply chain visibility.

Track real-time cryptocurrency prices across exchanges with historical

This skill enables Claude to track and optimize resource usage across an application stack.

Define and track SLAs, SLIs, and SLOs for service reliability including availability, latency, and error rates.

Builds trade area and catchment analysis workflows in CARTO.

Query TradingView market data through the bundled tradingview MCP server without a desktop app or login.

Eliminates AI writing patterns, translationese, and Mainland Chinese terms to produce natural, authentic Traditional Chinese copy for…

Traefik changes since training cutoff (latest: 3.6.9) — multi-layer routing, Redis rate limiter, p2c/leasttime LB strategies, fast proxy…

Extract clean article text, metadata, and structured content from web pages using the Trafilatura command-line tool or Python API.

Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions;

Help address review/issue comments on the open GitHub PR for the current branch using gh

Searches X/Twitter for real-time perspectives, dev discussions, product feedback, breaking news, and expert opinions using the X API v2.

Train or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval…

Translate a document into another language by re-authoring it so it reads as if it had been written in that language first, not mapped…

Corrects speech-to-text transcription errors in meeting notes, lectures, and interviews using dictionary rules and AI.

After the learner demonstrates understanding of a concept, present near-transfer and far-transfer challenges.

This skill should be used when building payment systems, implementing token transfers, or adding ENS/social handle resolution.