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Found 2,638 Skills
Use this skill when working with Mass Entity, MassEntity, Mass AI, MassProcessor, MassFragment, MassTag, MassObserver, MassSpawner, MassCrowd, Mass ECS, entity archetype, ForEachEntityChunk, FMassEntityQuery, FMassEntityManager, ISM crowd, or large-scale entity simulation in Unreal Engine. See references/mass-entity-patterns.md for processor and observer templates. See references/mass-fragment-reference.md for built-in fragment types.
This applies when working with PUDU CloudVeil (Yunyin) OpenAPI, SSO, SM2, data board statistics, robot maps, robot status, robot tasks, robot control, callbacks, dispatch, order-to-person, or assets/*.openapi.json.
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.**
Build and deploy a Next.js, Bigfish (@alipay/bigfish), or Vite project to the Morphe service (https://morphe.zenmux.app), targeting a linux-x64-gnu runtime. Use when the user asks to deploy, ship, publish, or release a Next.js, Bigfish, or Vite app to Morphe, run "morphe deploy", or otherwise push a build to the Morphe / zenmux platform. Handles login, framework detection, Next.js standalone validation / config fixing, Bigfish static-server wrapping, Vite SPA static wrapping or custom-server (server.ts/js) esbuild bundling, building, zipping, OSS upload, CRC64 checksum, .morphe.json management, and the deploy API call.
Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
Creates a new Linear issue from a free-form description. Drafts a structured title and body, picks team/project/labels/priority from the connected workspace, shows the draft to the user for approval, then creates the ticket. Use when the user asks to "create a Linear ticket", "file an issue", "make a ticket", "open an issue in Linear", or any request to log a new bug/feature/task.
End-to-end retail ETL pipeline using Medallion Architecture (Bronze/Silver/Gold) with TSQL, PySpark, and Airflow for inventory, sales, and supplier data processing
Verify in-text citations, references, author identities, year disambiguation, DOIs, and specified formatting rules; does not assess whether sources support claims. Use when the user asks for "check citation format", "verify in-text citations and references", "check authors with the same surname", "conduct a citation audit", or requests the rw-citation-audit workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Convert evidence gaps, conflicts, and anomalies into traceable candidate innovation points, and screen them based on contribution, feasibility, and falsifiability criteria. Use when the user asks for "finding research innovation points", "generating research directions from literature gaps", "screening candidate innovation points", "brainstorming research directions", or requests the rw-research-novelty workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Extract academic tone rules from the corpus provided by the user in this round or the current manuscript, and make minimal adjustments. Use when the user asks for "Extract my PhD tone", "Check if the paper sounds like me", "Preserve author fingerprint", or requests the rw-phd-tone workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Verify whether the analysis units, replication levels, statistical methods, and result reports in the research are consistent, and do not treat report review as re-analysis. Use when the user asks for "check statistical reports", "verify n and replicate experiments", "review statistical methods and results", or requests the rw-statistics-audit workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Use the local `5dive` CLI on a 5dive runtime VM to spawn, inspect, send to, and tear down sibling agents. Trigger when the user wants a worker, sub-agent, side task, parallel run, fan-out, or to delegate — or names a sibling agent ("ask X", "ping X", "tell X", "hand off to X", "coordinate with X"); confirm it exists via `5dive agent list --json`, then `agent send`. Also for inspecting/restarting/pairing an existing agent, a machine-readable health check (`5dive doctor --json`, `5dive selfcheck --json`), a task's causal history (`5dive trace <id|DIVE-N>`), the current model id per alias (`5dive models`), the host-shared task queue + org chart (`5dive task`, `5dive org`), grouping a multi-task effort under a project (`5dive project add`, `task add --project`), recurring/scheduled work (`task add --recurring`, `5dive heartbeat`), parking a question on a human (`task need`, risk-tiered via `--tier`) or snoozing work (`task park --wake`), searching the team's accumulated memory/wiki (`5dive memory search`) or compiling a durable one into it (`5dive memory add`), reading fleet health / token burn / the daily standup (`5dive supervisor`, `5dive usage`, `5dive digest`), building or editing multi-agent loops — a relay where each step hands off automatically with optional human gates (`task loop start`/`loop ls`) or a maker→verifier review loop (`task add --verifier`, `task reject`, `task loops`), or decomposing an outcome into a guardrailed task DAG (`5dive goal add`) — hiring a ready-made persona off the agent market (`5dive market`, `5dive hire --from-market`) or firing one (`5dive fire`), declarative fleets (`5dive up`, `5dive team import`), hosting a CrewAI crew (`5dive crew`), controlling agents on OTHER registered boxes (`5dive fleet`), running a self-steering objective bound to a live metric (`5dive objective`, `objective replan`), convening a governance vote (`5dive council convene`, `council gate-clear`, `council schedule add` for a recurring convene), the onboarding wizard (`5dive company`), or a delegated GitHub push-for-review (`5dive push`, needs `agent create --can-push`). When a request came over a chat channel (Telegram/Discord `<channel>` tag) and another agent should handle it, pass the chat context via `--reply-to-chat=<id> --reply-to-msg=<id>` so that agent replies from its own bot — don't relay. Always prefer `5dive` over running coding CLIs by hand.