Quick reference for fp-ts types. Use when user asks which type to use, needs Option/Either/Task decision help, or wants fp-ts imports.

ALWAYS use this skill when committing code changes — never commit directly without it. Creates commits following Sentry conventions with proper conventional commit format and issue references. Trigger on any commit, git commit, save changes, or commit message task.

Use when reviewing a pull request, to check for logic bugs, style consistency, and security concerns and summarise the findings for the author.

React and Next.js performance optimization guidelines from Vercel Engineering. Use when writing, reviewing, or refactoring React/Next.js code involving components, Next.js pages, Server Components, Server Actions, data fetching, bundle size, rendering behavior, or performance improvements.

Implement, refactor, review, or explain `@base-ui/react` in React applications. Use when working with Base UI components or utilities.

Use when the user asks about Liran Tal's talk at AI Native DevCon on skills security — including questions about the lethal trifecta / toxic flows, the Snyk research finding ~30% of ~4,000 Glow skills had security issues, malicious skill examples (SkillGuard, fake Vercel deployment skill, "buy anything", invisible-character Trojan Source skills), the confused-deputy problem, acceptance fatigue, parallels to NPM supply-chain attacks, or how to think about reviewing and sandboxing AI agent skills.

Use when the user asks about the "Welcome to AI Native DevCon" talk introducing Slick (slick.com) — a browser-native agent that controls the browser it runs in. Covers Slick's architecture (sprinkles, scoops, licks, the cone), how it uses HTTP / Chrome Debug Protocol / WebRTC, pyagent as the agentic loop, skills as "step zero of agent enablement", MCP and webMCP support, remote-controlling Electron apps (Slack, Teams, Claude desktop) via Slick Star, ad hoc generative UI, OAuth token handling, and verbatim quotes from the talk. Also use when the user wants to apply this browser-native agent approach to their own work.

Use when the user asks about Maximiliano Firtman's ("Maxi") AI Native DevCon talk on Web MCP and the agentic web — including questions about how Web MCP differs from MCP, exposing frontend tools to AI agents, the imperative vs declarative Web MCP APIs, tool design guidance (name/description/input schema/execute), the Chrome 149 origin trial, using Chrome DevTools MCP or Puppeteer as a bridge today, the Doom demo, or applying Firtman's "pick one high-value page state" adoption approach to current work.

当用户明确要求"标书QC/质量控制/润色前质检/引用真伪核查/篇幅与结构检查"时使用。对 NSFC 标书进行只读质量控制：并行多线程独立检查文风生硬、引用假引/错引风险、篇幅与章节分布、逻辑清晰度等，最终输出标准化 QC 报告；中间文件默认归档到 `project_root/.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/nsfc-qc/{yyyy-mm-dd-hh-mm}/`，并兼容 legacy `.nsfc-qc/` 读取/清理。

当用户明确要求“写/生成 NSFC 预算说明书”“写预算说明”“生成 budget.tex / budget.pdf”“写国自然预算 justification”时使用。基于用户标书正文或补充材料，输出一份可提交的预算说明书 LaTeX 项目并渲染 `budget.pdf`。若用户未指定工作目录，必须暂停并先要求其指定。⚠️ 不适用：用户只是想了解预算原则；用户仅要预算表数字而不写说明书；或用户是 2026 青年 A/B/C 默认包干制且无需预算说明书的场景。

智能数据采集技能，用于从图片或文档（PDF、Word、Excel）中提取结构化数据，基于知识网络完成字段映射，生成SQL并写入数据库。当用户提到"数据采集"、"从文档提取数据"、"图片转数据"、"数据导入"、"文档数据入库"、"批量数据提取"或需要从非结构化文件中提取结构化数据并存储时，自动使用此技能。

Guides creation of BKN (Business Knowledge Network) definition files following v2.0.1 spec. Covers network, object_type, relation_type, action_type, concept_group. Use when creating knowledge networks, BKN files, object types, relation types, action types, concept groups, or when user asks to model business knowledge in BKN format. When ontology-core is also loaded, use it to run ontology CLI (bkn push) after files exist.

腾讯会议：会议管理与音视频协作助手。预约/创建/修改/取消会议、查询会议详情与会议号转换、查看参会成员/受邀人/等候室成员、查询用户会议列表（即将开始/进行中/已结束）、查询录制列表与下载地址、获取转写全文/段落/搜索、获取AI智能纪要（支持多语言翻译）、录制权限申请（预览+提交两步流程）、时间转换与版本检查、Agent意见箱反馈上报。当用户需要预约或管理腾讯会议、查看参会人员、查询会议录制或转写内容、获取智能纪要时使用；当用户访问录制相关内容（下载地址/转写/智能纪要）出现无权限错误时，自动发起录制权限申请流程；当Agent遇到以下任何情况时必须立即触发submit_feedback：工具缺失（功能不存在）、工具报错（返回错误码）、能力不足（参数/功能限制）、结果不符预期（数据异常）、改进建议（功能优化）；如果用户提供的是9位会议号而非meeting_id，优先使用get_meeting_by_code转换后再操作。不要在以下场景触发：日程管理（非腾讯会议日程）、即时通讯/聊天、腾讯文档操作、企业微信审批流程、电话/PSTN拨号、视频剪辑或视频编辑、其他视频会议平台（Zoom/Teams/飞书/钉钉）。

Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.

Compose one publication-grade multi-panel figure. Entry from a one-line claim + data files, OR from an existing figure via `derive_outline_prompt` (you read the PNG). Runs a per-figure loop: outline (12-col grid, per-panel ask + label_budget) → render each panel with `panel_task` (loading `figure-style`), one at a time or parallelized → tile + stamp letters with `compose_figure` → adversarial composite self-review with two-tier feedback (Tier-1 outline_revisions / Tier-2 per-panel violations) → regen affected panels, ≤3 rounds. Helpers: panel_task / compose_figure / compose_crops / composite_review_task / derive_outline_prompt. For one standalone plot use `figure-style`; for whole-paper figure ordering use `paper-narrative`.

Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org `biohub`. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.

Structure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.

Grida AI agent system work: `@grida/daemon` (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and `@grida/agent` (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for `packages/grida-daemon/**`, `packages/grida-ai-agent/**`, desktop sidecar protocol changes, agent chat transport, and bugs in agent state or streams. For pure Electron window, preload, menu, deep-link, or CDP work, use `desktop`.

Use this skill when reading video-analytics metrics, incidents, alerts, and sensor data via the VA-MCP server (port 9901). Not for live VLM or incident-range narrative reports.

NVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with occupancy completion. Built on a VGGT backbone with a Mask2Former-style head and 3D frustum reconstruction. Use when training, evaluating, exporting, or running inference for a TAO NVPanoptix3D model. Trigger phrases include "train NVPanoptix3D", "panoptic 3D reconstruction", "3D scene segmentation", "occupancy completion".