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Found 1,018 Skills
VeChainThor node internals — architecture, consensus (PoA/PoS/BFT), built-in contracts, REST API, storage, P2P networking, block production, transaction lifecycle, reward distribution, staking, and contributing to the Go codebase.
Use when starting task work that needs branch isolation, before planning or coding — creates a worktree branching from current remote main with freshness verification and project setup
Use when an approved plan exists and needs execution, or when a hotfix/one-sentence scope needs direct TDD implementation — dispatches subagents per task, validates, reports
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.
Route issue-running automation through a deterministic control plane that selects agent + model from registry, can coordinate multiple safe parallel agents, and executes the unified run-agent runner.
Retrieve full historical end-of-day price data for market indices using Octagon MCP. Use when analyzing index performance over time, tracking market trends, calculating returns, and understanding market context for individual stock analysis.
Retrieve the latest stock grades and ratings from top analysts and financial institutions using Octagon MCP. Use when tracking analyst upgrades, downgrades, rating changes, and institutional sentiment over time.
Press photos into wire, web, print, social packs.
Selfie to four polished headshots for any use.
Drive the Duvo public API from the terminal via the `duvo` CLI (`@duvoai/cli`). Use when the user wants to script Duvo — managing agents, runs, cases, queues, files, skills, connections, Clarity processes, or hitting an arbitrary endpoint via `duvo api` — instead of clicking through the Duvo web UI or hand-crafting `curl` calls.
Owns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Two responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and workspace are in place, and (2) run ruff against any Python files Claude has just generated or edited. Stops at "the touched files pass `ruff check`." TRIGGER when (any of these): (1) a Python file was just created or edited via Write / Edit / MultiEdit — invoke this skill before declaring the task done so ruff is run on the touched files; (2) a fresh ML workspace was just scaffolded by `organize-ml-workspace` and the project has no `ruff.toml` at its root yet — drop the bundled template; (3) the user asks about lint, format, docstring style, or reaches for `black` / `isort` / `flake8` / `pydocstyle` (redirect to ruff — the stack's canonical linter, owned by `data-science-python-stack` Tier 1). SKIP when: the project is non-Python; the only edits in this turn are to Markdown / TOML / JSON / YAML; the file lives in a third-party vendored directory the user doesn't own. HOW TO USE: run ruff manually on the files you just touched — do not configure a PostToolUse hook for this. **Read the "Stop conditions" block and emit the Pre-flight checklist as visible text in your response — both are mandatory before running ruff.**
Audit an AI agent skill for security risks before installing or trusting it. Runs a deterministic scanner (regex patterns, Python AST analysis, source-to-sink taint tracking, and YARA signatures) and then reasons about intent — catching prompt injection, credential exfiltration, persistence, memory poisoning, malicious code, supply-chain risks, and description-vs-behavior mismatch. Make sure to use this skill whenever the user wants to scan, audit, vet, review, or check the safety of a skill, plugin, SKILL.md, or agent tool — whether it is a local folder, a zip/.skill file, or a cloned repo — and whenever someone asks "is this skill safe to install?".