القائمة
Communication standards for explaining technical concepts to different audiences. Use when presenting results, writing explanations, or preparing presentations.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
DEEP multi-step research harness. Decomposes queries into sub-questions, executes parallel web searches via Pieces MCP, iteratively refines with gap detection, and synthesizes cited reports. Architecture inspired by GPT Researcher (27.6k stars), Vane/Perplexica (35.2k stars), and Gemini Deep Research. Use when user asks for deep research, investigation, analysis, comparison, or any task requiring exhaustive web research.
DEFAULT THINKING MODE — not a feature, but how the agent operates. Every task gets innovation-overdrive thinking: research, ground, reflect on contradictions, propose, then build. This is the agent's identity, not a command. Integrates MiMo-Code's 6-phase memory consolidation.
Chain execution manager: validates dependencies, enforces order, tracks violations. Use to verify that all required skill chains were executed and to get the correct execution order.
API design patterns, REST conventions, and endpoint standards. Use when creating or modifying API endpoints. Covers routing, request/response patterns, error handling, and versioning.
Architectural design, system patterns, and dependency management. Use when designing new modules, refactoring existing systems, or making architectural decisions. Covers layering, coupling, cohesion, and design patterns.
Trigger-driven automation definitions and runner management. Use when creating, running, or managing skill-based automation pipelines.
| name | communication |
| description | Communication standards for explaining technical concepts to different audiences. Use when presenting results, writing explanations, or preparing presentations. |
| chains_with | ["automated-learning"] |
Example: "Our risk model shows a 1-in-20 chance of losing more than 1.36% in a day. That's within acceptable bounds."
Example: "VaR 95% is -1.36% from historical simulation, $10,716 from hybrid MC. The difference is methodology: one uses past returns, the other simulates forward."
Example: "We chose GARCH(1,1) over EGARCH for simplicity — the asymmetry didn't justify the complexity for our 14-asset universe at p<0.05."
