数据分析、机器学习、LLM 应用、提示词设计（9123 个）
Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.
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Auto-generates a changelog from git commits, sprint data, and design documents. Produces both internal and player-facing versions.
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Analyzes game balance data files, formulas, and configuration to identify outliers, broken progressions, degenerate strategies, and economy imbalances. Use after modifying any balance-related data or design. Use when user says 'balance report', 'check game balance', 'run a balance check'.
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Unity 6 ECS/DOTS development guide. Use when working with Entity Component System, data-oriented design, Jobs system, or Burst Compiler. Covers Entities, IComponentData, ISystem, EntityManager, baking, Jobs, and Burst. Based on Unity 6.3 LTS documentation.
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Unity 6 AI and navigation guide. Use when working with NavMesh, pathfinding, NavMeshAgent, NavMeshSurface, NavMeshObstacle, off-mesh links, or Unity Sentis (ML model inference). Covers AI navigation package, runtime NavMesh baking, and common AI patterns like state machines and behavior trees. Based on Unity 6.3 LTS documentation.
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Unity 6 physics development guide. Use when working with Rigidbody, colliders, raycasting, triggers, collisions, joints, or physics simulation. Covers PhysX 5 (3D) and Box2D (2D) physics, FixedUpdate timing, layer masks, and contact data. Based on Unity 6.3 LTS documentation.
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Unity ScriptableObject patterns for data management, configuration, and runtime systems.
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Unity data-driven design architecture. ScriptableObject config hierarchies, JSON data pipelines, designer handoff workflows, data versioning and migration, Inspector attributes for self-documenting configs. DECISION format: WHEN/DECISION/SCAFFOLD/GOTCHA. Based on Unity 6.3 LTS.
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Plan a feature before writing any code. Use this skill at the START of non-trivial feature work — when the user says they want to "add", "build", "implement", "create", "develop", or "ship" a feature, endpoint, component, page, service, or capability. Especially trigger when the user's prompt is short or under-specified ("add a dashboard", "build an auth flow", "let's do user activity reports") — those need planning, not direct execution. The skill walks through requirements clarification, codebase exploration, sketches a Mermaid architecture/flow diagram of the proposed design, and produces a plan.md document the user can hand off to a fresh AI session for execution. Skip only when the change is genuinely trivial (typo fixes, single-line tweaks, renames). When in doubt, plan.
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Guidance for Tauri v2 NFC plugin with session handling and data validation.
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Guidance for Tauri v2 SQL plugin setup, migrations, and safe query access.
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Guidance for Tauri v2 stronghold plugin with encrypted storage and sensitive data handling.
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Generate fantasy character names in zh-TW with original spelling and etymology, across human, elf, dwarf, orc/beastfolk, and halfling naming traditions. Use when the user needs a name for a character, NPC, party member, villain, shopkeeper, or monster, asks to think of, suggest, or rename such a character, names entities for a MUD/TRPG/game world or worldbuilding document, or writes lore, quests, presets, or seed data that require in-world personal names.
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Tunes noisy detections by analyzing historical alert data to quantify false-positive sources, recommend allow-list filters and threshold adjustments, and measure precision impact. Activates for requests to tune a detection, reduce false positives, or analyze alert noise and recommend filters.
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Pivots on indicators of compromise across multiple data sources by correlating a seed set of IOCs against logs to find co-occurring indicators, hosts, and timeframes that expand the investigation. Activates for requests to pivot on IOCs, correlate indicators across data sources, or expand an investigation from a seed indicator set.
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Hunts for pre-exfiltration data staging and archiving by detecting archive-tool execution (rar, 7z, zip, tar), large compressed files written to staging directories, and collection into a single location before transfer. Activates for requests to hunt data staging, detect pre-exfil archiving, or find collection and compression before exfiltration.
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Hunts for unusual outbound network connections by flagging direct-to-IP traffic, uncommon ports, rare destinations, high data-egress ratios, and connections from unexpected processes in network telemetry. Activates for requests to hunt unusual outbound traffic, detect suspicious egress, or find anomalous external connections.
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Detects DNS-based tunneling and data exfiltration in DNS logs: scoring high query volume to single domains, long/high-entropy subdomains, unusual record types, and encoded payload labels. Activates for requests to hunt DNS tunneling, detect DNS exfiltration, or analyze suspicious DNS query patterns.
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Frames a structured, testable threat-hunting hypothesis: grounding it in adversary behavior and available telemetry, defining the data sources and detection logic, and setting success criteria and outcomes. Activates for requests to start a threat hunt, write a hunt hypothesis, or plan a hypothesis-driven hunt.
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Analyzes suspected webshells (PHP, ASPX/ASP, JSP) by detecting dynamic-execution sinks, input-to-sink data flow, and common encoder/obfuscation chains, then decoding obvious layers to reveal the command interface. Activates for requests to analyze a webshell, identify a PHP/ASPX/JSP backdoor, or deobfuscate server-side malicious scripts.
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Builds Zeek-based network hunting analytics by writing scripts and analyzing Zeek logs (conn, dns, http, ssl, files) to surface long connections, rare JA3s, suspicious downloads, and beaconing. Activates for requests to build Zeek analytics, write a Zeek hunting script, or analyze Zeek logs for threats.
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Analyzes banking trojan webinject configurations to extract targeted institutions, injected JavaScript/HTML, and data-theft hooks, mapping the fraud workflow. Activates for requests to analyze banking trojan webinjects, parse a webinject config, or map targeted banks and credential-theft injections.
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Set up GEPA prompt optimization for an ORC workflow
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Set up LLM-as-judge evaluation for ORC workflows
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