Push the current branch and open a draft PR for Meshtastic-Android the repo way — baseline verified first, body drafted per .github/copilot-pull-request-instructions.md (WHY-first, categorized changes), screenshots embedded via commit-pinned raw URLs. Use whenever work is ready to go up as a PR.

Wait for UI element or window to appear. When you need to wait for dialog to open, loading to complete, or synchronize with application state before next action. Default timeout is 10 seconds.

Use when a task asks why code is built a certain way, proposes architectural changes, compares implementation approaches, or mentions decision markers such as WHY, DECISION, TRADEOFF, or ADR in a Repowise-indexed repository.

**WORKFLOW SKILL** — Create, update, review, fix, or debug VS Code agent customization files (.instructions.md, .prompt.md, .agent.md, SKILL.md, copilot-instructions.md, AGENTS.md). USE FOR: saving coding preferences; troubleshooting why instructions/skills/agents are ignored or not invoked; configuring applyTo patterns; defining tool restrictions; creating custom agent modes or specialized workflows; packaging domain knowledge; fixing YAML frontmatter syntax. DO NOT USE FOR: general coding questions (use default agent); runtime debugging or error diagnosis; MCP server configuration (use MCP docs directly); VS Code extension development. INVOKES: file system tools (read/write customization files), ask-questions tool (interview user for requirements), subagents for codebase exploration. FOR SINGLE OPERATIONS: For quick YAML frontmatter fixes or creating a single file from a known pattern, edit the file directly — no skill needed.

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

Twenty-minute conversational diagnostic for assessing a company's world-model readiness. Use when the user wants to map their company to the right world-model paradigm, identify where the highest-fidelity signal lives, audit the boundary layer between facts and interpretation, flag simulated-judgment exposure, and leave with a first/second/third build sequence. Works in plain chat and compounds when Open Brain search/capture tools are present.

Use when the user wants a weekly structural diff on AI, software, or another fast-moving market. Starts from 10 suggested categories and 30 suggested companies when no watchlist exists, then adapts the scan using Open Brain memory, current priorities, and prior digests. Best for prompts like "run my weekly signal diff", "what changed this week that matters to me", "track this market", or "turn this week's news into structural shifts". Optional live search upgrade: if OpenRouter access is available, prefer the Perplexity Sonar family for fresh web-grounded retrieval with citations.

Decision-grade workflow for synthesizing a source set into clear findings, contradictions, confidence markers, gaps, and next questions. Use for prompts like "synthesize these sources", "turn this research into a brief", "what are the key findings", or "where do these sources disagree". Best when you have a research question, a defined audience, and a set of source materials. Optional Open Brain search and capture can pull prior context and store the final synthesis.

Use when a user asks to read, analyze, summarize, or extract from a heavyweight file such as PDF, DOCX, PPTX, XLSX, CSV, or TSV. Convert the file into markdown or CSV first, generate a lightweight index, and only spend model tokens on the compressed artifact. Trigger on requests like "read this PDF", "look through this spreadsheet", "summarize this deck", or any time raw file ingestion would waste tokens.

Syncs Claude Code's local memory system to Open Brain. Triggers whenever memories are saved via dreaming, autodream, or explicit "remember this" requests. After every local memory file write, captures the same content to Open Brain via mcp__open-brain__capture_thought so that memories are accessible from all connected AI clients (ChatGPT, Claude Desktop, Codex) and across all devices. Trigger on: memory saves, autodream, dreaming, "remember", "save to memory", or any write to the .claude/projects/*/memory/ directory.

Regenerate and refresh the curated agent model catalog (the label/description/pricing/ratings behind the agent model picker). Use when the pinned @earendil-works/pi-ai version bumps, when a Claude Code build changes its accepted alias set, or before a release when the curated Claude/Pi facts (lineup, pricing, ratings) need refreshing from current public sources. Owns the data files under sdks/python/agenta/sdk/agents/data/; never edits capabilities.py logic.

Expert guidance for Geistdocs, Vercel's documentation template built with Next.js and Fumadocs — MDX authoring, configuration, AI chat, i18n, feedback, deployment. Use when creating documentation sites, configuring geistdocs, writing MDX content, or setting up docs infrastructure.

Planning skill that helps the developer pick the right Twilio messaging channel — SMS, MMS, RCS, or WhatsApp — for a given use case. Qualifies intent across content type, geography, use case (marketing / notifications / OTP / support), cost model, and brand presence. Use when the developer asks "which channel should I use", "SMS vs RCS vs WhatsApp", mentions a country or region, asks about branded messaging, rich content, or fallback — and proactively when the developer says "send SMS" but their use case (rich content, international reach, branded experience) would benefit from a different channel.

Planning skill for building customer service and support systems. Qualifies the developer's needs across the support ladder (self-service → AI agents → contact center), channel mix, and scale to recommend the right Twilio architecture. Handles both "build me a call center" and "add an IVR to my existing support line."

Build, run, deploy, and evaluate OpenAI Agents SDK apps from Codex. Use when the user asks to create or adapt an Agents SDK app, build from a prompt or Codex thread, prepare a runnable agent prototype, add a focused eval harness, or deploy locally through the Agents SDK Deployment Manager.

Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.

Dispatch bulk RNA-seq requests to FASTQ-to-count QC or count-matrix differential-expression skills using nf-core/rnaseq, STAR, Salmon, featureCounts, MultiQC, and R/Bioconductor workflows.

Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, or isolated security scanners. Also applicable when the workload needs long-lived sessions, a real port-listening server (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing.

Evaluates, configures, and migrates workloads to AWS Lambda Managed Instances (LMI). Runs Lambda functions on EC2 instances in the user's account while AWS manages provisioning, patching, scaling, routing, and load balancing. Triggers when queries mention Lambda Managed Instances, LMI, capacity providers, multi-concurrent execution environments, EC2-backed Lambda, persistent Lambda instances, PerExecutionEnvironmentMaxConcurrency, CapacityProviderConfig, cold start elimination via dedicated instances, migrating standard Lambda to managed instances, or cost comparison between standard Lambda and LMI with Savings Plans or Reserved Instances.

Configures AWS Resilience Hub v2 for multi-account resilience management across an AWS Organization. Covers the per-service cross-account permission model, cross-account IAM roles, and centralized assessment from a single account. Applies when the user wants to set up org-wide resilience or assess workloads that span multiple AWS accounts.