بنقرة واحدة
context-engineer
Optimize prompts and context windows to reduce token usage while preserving quality.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Optimize prompts and context windows to reduce token usage while preserving quality.
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
Sends messages between agents, broadcasts to channels, and retrieves message history for inter-agent communication.
Spawns, manages lifecycle, and terminates autonomous AI agents from the 40+ built-in agent catalog.
Animated desktop character state machine for Sven's Tauri companion app. Manages character form (ORB, ARIA, REX, ORION), state transitions (idle→thinking→speaking→celebrating), walk cycles, thought bubbles, sound effects, and real-time agent event sync.
Multi-model deliberation system. Sends queries to multiple LLMs simultaneously, has them peer-review each other's responses anonymously, then a chairman model synthesizes the best answer. Supports configurable council composition, voting strategies, and cost tracking.
Interactive educational autograd engine — port of Karpathy's micrograd. Build, train, and visualise tiny neural networks step-by-step to learn how backpropagation works.
Runs benchmark suites against models, tracks ELO rankings, manages A/B tests, and generates performance reports.
| name | context-engineer |
| description | Optimize prompts and context windows to reduce token usage while preserving quality. |
| version | 0.1.0 |
| publisher | acmecorp |
| handler_language | typescript |
| handler_file | handler.ts |
| when-to-use | Use when the user wants to optimize prompts, reduce context size, or improve token efficiency. |
| inputs_schema | {"type":"object","properties":{"action":{"type":"string","enum":["optimize","analyze","chunk"]},"text":{"type":"string"},"max_tokens":{"type":"number"},"strategy":{"type":"string","enum":["remove_redundancy","summarize_sections","prioritize_recent","extract_key_facts"]}},"required":["action","text"]} |
| outputs_schema | {"type":"object","properties":{"result":{"type":"object"}}} |
Optimizes prompts and context windows for token efficiency. Analyzes content for redundancy, prioritizes key information, and restructures for maximum information density.