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Found 2,139 Skills
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
This is used when users or Agents need to obtain, query, synchronize, analyze or export A-share market data, financial reports, valuations, indices, sectors, public funds, featured data or local DuckDB data via Hithink Finance Data Service, or need to select, install, configure, diagnose REST API, MCP, hithink-finance CLI, Python SDK/marketdb.
Finds and deletes "Captain Obvious" tests — tests that can never fail or check nothing. It catches assertions the type checker already guarantees (typeof/isinstance/toBeDefined on typed values), assertion-free tests, tautologies (expect(true).toBe(true), assert x == x, len >= 0), arrange-assert echoes (const x = 5; expect(x).toBe(5)), mock-echo tests, unawaited async assertions, dead/swallowed/conditional assertions, overly-broad pytest.raises(Exception), and duplicate test bodies. Use whenever the user wants to clean up a test suite, remove redundant/useless/tautological/AI-generated tests, mentions tests that "never fail" or "test nothing", or says "captain obvious". Works on TypeScript (Jest/Vitest/bun:test) and Python (pytest + mypy). The detection is fully deterministic — always run the bundled scripts, never scan test files one by one yourself.
This skill should be used when users want to install, set up, or integrate ZeroEval into their AI application, agent, or pipeline. It covers SDK setup (Python and TypeScript), first-run tracing, ze.prompt migration, and judge recommendations. For non-SDK languages or direct API/OTLP ingestion it routes to the custom-tracing skill. Triggers on "install zeroeval", "set up zeroeval", "add tracing", "integrate zeroeval", "ze.prompt", "add judges", or "monitor my AI app".
NVIDIA DeepStream SDK 9.0 development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker integration.
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness — currently Code Mode, which collapses many tool calls into one sandboxed Python execution. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
Universal release workflow. Auto-detects version files and changelogs. Supports Node.js, Python, Rust, Claude Plugin, GitHub Releases, annotated tags, historical release backfill, and generic projects. Use when user says "release", "发布", "new version", "bump version", "push", "推送", "release notes", "GitHub Release", or "回填 Release".
Read-only multi-agent review of a GitHub Pull Request, with the synthesized report posted back as a PR comment so the author is notified. Use when the user wants to review a GitHub PR (github.com or GitHub Enterprise) and post a structured review back to the PR conversation. Auto-detects the PR from the currently checked-out branch when no locator is supplied. Requires `gh`, `uuidgen`, `jq`, and `uv` or `python3` on PATH. Activates the `review-anvil` engine in read-only mode and orchestrates the shell helper for posting.
Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. Use this whenever someone raises a Qdrant problem or question — slow or degraded search, high or growing memory / OOM crashes, optimizer stuck or slow, indexing slowness, scaling and sharding decisions (node count, QPS, latency, multitenancy, vertical vs horizontal), poor or irrelevant search results, hybrid search and reranking, embedding-model migration, version upgrades and compatibility, monitoring and observability (Prometheus, Grafana, health checks, /metrics, /telemetry), deployment choices (local, Docker, self-hosted, Qdrant Cloud, embedded), or client-SDK questions (Python, TypeScript, Rust, Go, .NET, Java). Trigger especially when the context is clearly a Qdrant cluster, collection, or vector-search deployment. Always prefer this skill over answering from memory: it pulls current, authoritative guidance and only the relevant context.
Installs and configures OpenTelemetry auto-instrumentation for applications written in Java, .NET, Node.js, Python, Ruby. Use when instrumenting applications with opentelemetry auto-instrumentation, auditing existing auto-instrumentation implementations, migrating from vendor locked instrumentations to OpenTelemetry, or checking for latest versions of instrumentation libraries.
Trading expert for Forex/CFD, indices (DAX, NASDAQ, S&P500), MQL5, Pine Script v5, MT5 Python API. Use for: trading strategies, technical analysis, risk management, Expert Advisors, custom indicators, backtesting, copy trading, prop trading rules, Smart Money Concepts, ICT, Ichimoku Kinko Hyo, ŚWISTAK Fibonacci.
MANDATORY for static requests to find, identify, or list untested source files or modules, sources without tests, source-to-test pairing, test-gap worklists, or suggested test locations. Invoke even for a tiny package; do not substitute manual globbing. Uses Roslyn for C#/.NET and tree-sitter for Python, TS/JS, Go, Java, Rust, and Ruby. DO NOT USE FOR: line/branch coverage, CRAP risk, or grading existing tests.