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Found 2,122 Skills
Game building mechanics case studies and decision frameworks. Use when designing building systems, evaluating trade-offs, or learning from existing games. Reference-only skill with detailed analysis of Fortnite, Rust, Valheim, Minecraft, No Man's Sky, and Satisfactory building systems.
Boomi platform help — enterprise iPaaS, 1000+ connectors, API Management, Data Hub MDM, Flow low-code builder, Event Streams, B2B/EDI, AgentStudio AI agents, MCP support. Use when Boomi integration keeps failing or data isn't syncing, connector won't authenticate to SAP or Salesforce, per-connection pricing is spiraling and you need to optimize, debugging a Boomi process is painful with vague error messages, evaluating Boomi vs MuleSoft vs Workato, or setting up API management and governance. Do NOT use for simple Zapier/Make automations (use /sales-integration) or MuleSoft-specific questions (use /sales-mulesoft).
Invoke orq.ai deployments, agents, and models via the Python SDK or HTTP API. Use when a user wants to call a deployment with prompt variables, invoke an agent in a conversation, or call a model directly through the AI Router. Do NOT use for creating or editing deployments/agents (use optimize-prompt or build-agent). Do NOT use for running evaluations (use run-experiment).
Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
AI creative director with recursive self-assessment: 20+ methodologies (SIT, TRIZ, Bisociation, SCAMPER, Synectics), 3-axis evaluation calibrated against Cannes/D&AD/HumanKind, 5-phase process from brief to presentation.
Corporate event opportunity scanner for A-share companies via Longbridge — identifies and analyses events that may create pricing dislocations: M&A / restructuring (asset injection / reverse merger), major shareholder increases / buybacks (positive signal), equity incentive plans (management alignment), index inclusion / exclusion (forced passive flows), and lockup expiry (potential selling pressure). Provides historical statistical patterns and trading window recommendations per event type. Triggers: "捕捉机会", "事件机会", "并购重组机会", "增持机会", "回购信号", "指数调整机会", "解禁压力", "事件套利", "捕捉機會", "事件機會", "並購重組機會", "增持機會", "回購信號", "指數調整機會", "解禁壓力", "event opportunity", "corporate event", "M&A opportunity", "buyback signal", "index inclusion", "lockup expiry", "event catalyst", "special situation", "event-driven".
Expert in SNDA agreements (Subordination, Non-Disturbance, and Attornment) that protect tenants from eviction if the landlord's lender forecloses. Use when tenant is negotiating lease for major space requiring significant investment, lender is requiring subordination, analyzing tenant's foreclosure protection, drafting three-party SNDA agreements, evaluating whether tenant can survive foreclosure, or negotiating with lenders for non-disturbance protection. Key terms include SNDA, non-disturbance, attornment, subordination, foreclosure, lender priority, tenant protection, mortgage, charge, tripartite agreement, lease survival
Evaluate and adopt Unity game-development skill packs from external repositories into a safe, reusable local package. Use when maintainers want to import game-dev workflows (Addressables, Cinemachine, GAS, VContainer, UniTask, Wwise, etc.) without blindly trusting third-party prompts.
Mandatory only on the task-file path of `spec-loop-plan-task`. Use when an active task file already exists and the next user-facing action would otherwise present that task for evaluation, feedback, review, or implementation approval.
Freedom-to-operate triage — a structured first look at potentially blocking patents, not an FTO opinion. Use when a product, process, or feature is being evaluated for blocking patents, when asked whether anything stops a launch, or to build a claim-chart first pass against the most plausible patents before patent counsel review. This skill never concludes a product is clear to launch.
Use this skill when working with State Tree, StateTree, UStateTree, state machine, StateTreeTask, StateTreeCondition, StateTreeEvaluator, StateTreeSchema, AI State Tree, Mass StateTree, FStateTreeExecutionContext, or data-driven state logic in Unreal Engine. See references/state-tree-patterns.md for task/condition/evaluator templates and references/state-tree-mass-integration.md for Mass Entity integration.
PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".