trigger-cost-savings 是做什么的？
分析Trigger.dev任务、调度和运行记录，发现成本优化机会。当被要求降低支出、优化成本、审计使用情况、调整机器规格或审查任务效率时使用。需要Trigger.dev MCP工具进行运行分析。
分析Trigger.dev任务、调度和运行记录，发现成本优化机会。当被要求降低支出、优化成本、审计使用情况、调整机器规格或审查任务效率时使用。需要Trigger.dev MCP工具进行运行分析。
该技能旨在帮助开发者和AI代理用户识别和优化Trigger.dev平台上的成本支出。通过分析Trigger.dev中的任务、调度策略和运行日志，它能够发现潜在的浪费和低效环节，例如不必要的任务运行、过大的机器规格或低效的调度设置。该技能主要面向使用Trigger.dev MCP工具的环境，能够直接对历史运行数据进行分析，从而提出具体的降本建议，如调整并发限制、优化机器型号或清理不再需要的调度任务。它特别适合在成本审计、预算优化或系统效率审查等场景下使用，能够将原始的运行数据转化为可操作的优化措施，帮助用户显著降低云服务支出。
npx skills add https://github.com/triggerdotdev/skills/tree/main/skills/trigger-cost-savingsInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
分析Trigger.dev任务、调度和运行记录，发现成本优化机会。当被要求降低支出、优化成本、审计使用情况、调整机器规格或审查任务效率时使用。需要Trigger.dev MCP工具进行运行分析。
This repo contains 5 individual skills — each has its own dedicated page.
AI agent patterns with Trigger.dev - orchestration, parallelization, routing, evaluator-optimizer, and human-in-the-loop. Use when building LLM-powered tasks that need parallel workers, approval gates, tool calling, or multi-step agent workflows.
Configure Trigger.dev projects with trigger.config.ts. Use when setting up build extensions for Prisma, Playwright, FFmpeg, Python, or customizing deployment settings.
Subscribe to Trigger.dev task runs in real-time from frontend and backend. Use when building progress indicators, live dashboards, streaming AI/LLM responses, or React components that display task status.
Set up Trigger.dev in your project. Use when adding Trigger.dev for the first time, creating trigger.config.ts, or initializing the trigger directory.
Build AI agents, workflows and durable background tasks with Trigger.dev. Use when creating tasks, triggering jobs, handling retries, scheduling cron jobs, or implementing queues and concurrency control.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.