Instructions for declaring, formatting, emitting, testing, and styling diagnostic messages (errors, warnings, notes) in the Carbon toolchain.

Instructions for code formatting and style guidelines in the Carbon toolchain.

Instructions for registering, mapping, constant evaluating, and lowering builtin functions in the Carbon toolchain.

Instructions that **MUST** be followed when using Bazel or Bazelisk to build, test, and debug in the Carbon repository.

Guidelines and restrictions on shell commands and file manipulation tools for AI assistants.

Signals scout for PostHog web traffic. Watches per-channel session volume, attribution breakage, and landing-page health (bounce / 404 steps) against the site's own baseline, and files each validated divergence as a report in the inbox. Per-page web vitals have their own dedicated `signals-scout-web-vitals`.

Skill-hygiene scout for the team's PostHog skills store, read entirely via the MCP skill tools. Watches recently-changed skills — plus a slow rotation over the most-used, highest-leverage ones — for statically-verifiable authoring violations: vague descriptions, bloated bodies, dead bundled-file links, kitchen-sink scope, committed secrets. Files each non-compliant skill as a report in the inbox, with the copy-ready fix inside.

Signals scout for core product-analytics flows — funnels, retention, lifecycle, stickiness, and paths. Watches the team's saved flows for a derived-rate regression (conversion or retention sliding) while entrants hold, and files it as a report in the inbox.

Cross-product Signals scout. Looks for cross-product correlations and explores the surfaces the per-product specialist scouts don't cover.

Converts engineering analytics (PR / CI) data into saved PostHog insights, dashboards, and subscriptions, and explains how to query the product data directly with SQL. Covers discovering per-team GitHub warehouse tables via engineering-analytics-sources, replicating curated column semantics in HogQL, reading exposed engineering_analytics_* warehouse views where product logic is involved (CI cost, fingerprinted failure lines, commit attribution), saving queries with insight-create, and scheduling delivery with subscriptions-create. Use when asked to "save this as an insight", "put CI health / merge times on a dashboard", "email me PR throughput weekly", "chart CI cost", "track time to first review", "subscribe to these numbers", "alert on CI success rate", or "what data/tables/views does engineering analytics read". For ad-hoc CI and merge questions use diagnosing-ci-and-merge-bottlenecks; to investigate one specific CI failure use investigating-ci-failures.

处理 1c7/chinese-independent-developer 仓库的项目提交。 检查 issue #160 新评论、新开的 Issue、新开的 PR， 将有效项目添加到对应 README，关闭垃圾内容。 当用户要求“收录项目”“处理提交”“处理 issue”“跑一下列表”或运行中国独立开发者列表维护流程时使用。

Instructions for fetching current weather temperature data for Dubai, UAE from Open-Meteo API

Use the LLM Wiki plugin tools to maintain a cited local company wiki.

Reviews DeerFlow skill packages for readiness, triggers, safety boundaries, resources, and evidence. Invoke when users ask to audit, grade, or production-check an existing skill.

This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.

One-click contribution flow for OpenDesign (nexu-io/open-design) — even for non-coders. Pick one of four cards (ship a Skill or Design System you made with OD; translate docs; fix a typo / write a blog; report a bug), the agent validates and opens a PR (or issue) for you. Trigger words contribute to open design, ship my OD skill, ship my OD design system, translate OD docs, report an OD bug, od-contribute.

Join a Google Meet call, transcribe live captions, optionally speak in realtime, and do the followup work afterwards. Use when the user asks the agent to sit in on a meeting, take notes, summarize, respond in-call, or action items from it.

Publish sites to {slug}.here.now and store files in Drives.

Manus-style persistent file-based planning for AI coding agents: keeps task_plan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session recovery after /clear.

Manus-style persistent file-based planning for AI coding agents: keeps task_plan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session recovery after /clear.