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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`.

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Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.

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Use when the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Uses Gemini 3 Pro by default for state-of-the-art reasoning and coding.

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Reverse shell techniques playbook. Use when establishing remote shells including language one-liners, encrypted shells (OpenSSL/socat/ncat), web shells, PTY upgrades, file transfer methods, PowerShell shells, and Windows payload generation.

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Anti-debugging detection and bypass playbook. Use when reversing protected binaries that detect debuggers via ptrace, PEB flags, timing checks, or signal/exception handlers on Linux and Windows.

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Apply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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When the user wants to set up, debug, or interpret app install attribution — including SKAdNetwork (SKAN), Apple's AdAttributionKit, Google Play Install Referrer, MMPs (AppsFlyer, Adjust, Singular, Branch, Kochava), deep links, deferred deep links, conversion values, postback windows, or privacy thresholds. Use when the user mentions "SKAdNetwork", "SKAN", "SKAN 4", "AdAttributionKit", "AAK", "MMP", "AppsFlyer", "Adjust", "Singular", "Branch", "attribution", "conversion value", "postback", "Install Referrer", "deferred deep link", "iOS 14.5", "ATT", "App Tracking Transparency", "IDFA", or "I can't measure my ad campaigns". For paid campaign strategy, see ua-campaign and apple-search-ads. For analytics events, see app-analytics.

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Build the native (MSIX, isolated-session) OpenClaw Gateway from the latest openclaw/openclaw sources (or any ref, local checkout, or prebuilt openclaw.tgz), register it side by side with the Microsoft Store Gateway, and run Companion against it with OPENCLAW_NATIVE_GATEWAY_DEV_PATCH. Use when the user asks to test Companion with Gateway main, an unreleased Gateway change, or a source-built native Gateway, or to remove such a build.

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Adversarial dual-model code review that runs two AI models in parallel, cross-references findings, and produces a consensus severity table with fix confidence ratings. Use when asked for a thorough code review, adversarial review, dual-model review, confidence-rated review, or 'Hanselman review'.

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Structured code review through the shared OpenClaw agent-skills installation.

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Train and run models on Tinker (Thinking Machines) — LoRA and full fine-tuning, SFT with correct loss masking, RL/RFT with group-relative advantages and importance sampling, agentic RL over multi-turn tool-using agents, inference via the SamplingClient or the OpenAI-compatible endpoint, checkpoint management and export, every hyperparameter, and cost estimation from the live price table. Use this skill whenever the user mentions Tinker, tinker://, TINKER_API_KEY, console.tinker.ai, or the tinker CLI; wants to fine-tune, SFT, RFT, or RL a model on Tinker; asks about Tinker models, context windows, LoRA rank, sampling params, loss functions (cross_entropy, importance_sampling, ppo, cispo, dro), Datum construction, forward_backward or optim_step; wants to sample from, download, resume, merge, or export a Tinker checkpoint; or asks what a Tinker run will cost. Whenever Tinker work is initialized in a project, this skill also creates a TINKER_PRICING.md there so prices sit next to the training code. Reach for it even on vague asks like "train a model on this data" or "get inference working" when Tinker is the platform in play.

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Runs servers and corporate systems — patching, configuration baselines, change control, capacity, and the routine that prevents incidents. Use this to establish a patching cadence, standardize server configuration, plan a maintenance window, decide change control for infrastructure, or clean up systems that have drifted from any known state.

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Use the Crabbox wrapper for validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.

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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.

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Edit file by exact string replacement. Finds old_string and replaces with new_string. Safer and more token-efficient than write_file for modifying existing files. Auto-handles Windows CRLF line endings.

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Inspect window UI element tree structure for debugging and understanding interface layout. When you need to debug UI automation issues, understand application structure, or find correct element identifiers.

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Execute keyboard shortcuts. When you need to copy/paste (Ctrl+C/V), save files (Ctrl+S), close windows (Alt+F4), undo/redo (Ctrl+Z/Y), or select all (Ctrl+A).

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WeCom (Enterprise WeChat) CLI - official open-source CLI tool from WeCom. Covers 7 business categories: Contacts, Todos, Meetings, Messages, Schedules, Documents, Smartsheets. Built in Rust for macOS/Linux/Windows. Use when user wants to operate WeCom resources.

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Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.

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Builds clear, executable, and auditable inclusion and exclusion criteria for biomedical and clinical research protocols. Always use this skill when a user needs to translate a target population into operational screening rules tied to chart fields, time windows, tests, procedures, prior therapies, exclusions, and reviewable edge cases. Focus on protocol-stage precision, ambiguity reduction, auditability, and screening reproducibility rather than generic study design advice.

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Maps whether a biomedical research topic, subtopic, or study angle is truly saturated, superficially crowded, strategically occupied, or still open for differentiated entry. Use this skill when a user wants to know whether a hot medical research direction is already overworked, whether meaningful whitespace remains, whether major groups have already occupied the obvious claims, and whether the timing window is still open. Always distinguish popularity from true saturation, and distinguish cosmetic novelty from meaningful differentiating entry.

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Model OR-Tools paired pickup-and-delivery routing problems, including PDPTW, dial-a-ride, paratransit, patient transport, and courier jobs with same-vehicle pairing, precedence, capacity, optional connected service, rider time windows, and vehicle shifts.

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Build OR-Tools RoutingModel vehicle-routing models with transit matrices, dimensions, capacity constraints, time windows, optional visits, invalid-arc handling, search parameters, and route extraction.

日本語の概要は準備中です。原文の説明を表示しています。