Results for “uptimerobot”

Synthesize market breadth, regime, and flow signals into a unified capital commitment recommendation with exposure ceiling, bias, and action guidance.

Compares tracked job postings against the candidate profile to identify skill gaps and generate a prioritized learning plan with study resources. Triggers on: /upskill, upskill, skill gaps, what should I learn, learning plan

Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context).

Schedule reminders and recurring tasks that report back to the originating chat or session, with support for one-time, recurring, and timezone-aware jobs.

Track elapsed time from a set epoch with tamper-evident locking, supporting count-up, count-down, and count-between modes, milestones, and email notifications.

Turn a weak/cheap "Flash" model into a "Pro" performer by wrapping HKUDS UpSkill — captures agent session failures, has a strong Teacher model analyze them and draft a skill, then validates it against the weak Student model in a closed Ralph Loop (up to 3 rounds) before storing it for automatic reuse. Use when the user wants to install UpSkill, run `/upskill-init`, `/upskill-configure`, `/upskill-build`, `/upskill-run`, `/upskill-list`, `/upskill-status`, `/upskill-mode`, `/upskill-model`, `/upskill-remove`, or `/upskill-uninstall`, wants a cheap model to perform closer to a Pro model without switching, or wants a good session (success or failure) distilled into a validated skill. Triggers on: upskill, up-skill, flash to pro, teacher student distillation, ralph loop skill validation, distill agent failures into skills. Routes skill-quality ratcheting to `skill-autoresearch`, scaffolding to `write-a-skill`, and spec-compliance rewrites to `skill-standardization`.

Diagnose and optimize slow-loading, high-memory, or low-FPS USD scenes using a structured workflow with profiling, validation, and mutation phases.

Finetunes the NV-Generate-CTMR MR-brain diffusion UNet from user-supplied NIfTI training volumes using a wrapper that stages configs and delegates to upstream scripts.

Runs DNS, email security, SSL, WHOIS, and network checks by calling the dnsrobot.net API, with no API key required.

Zero-shot univariate time-series forecasting with Google's TimesFM foundation model, producing point forecasts and prediction intervals from CSV/DataFrame/array inputs, with a preflight system checker for RAM/GPU. Use to forecast any univariate series (sales, sensors, energy, vitals, weather) without training a custom model. Part of the AlterLab Academic Skills suite.

Use when a high-priority signal needs to reach the operator but doesn't fit the current conversation (off-hours wake, urgent error needing eyes, scheduled-tick discovery worth surfacing now). Routes via MIMIR_OPERATOR_ALERT_CHANNEL.

Implement BullMQ job workflows in NestJS. Use when building queue processors, redis-throttler, Upstash limits, idle polling, stalled jobs, and retention policies.

Upscale and enhance image and video resolution using AI

Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.

Optimize post-signup onboarding, user activation, first-run experience, and time-to-value with structured audits, flow design, and measurement plans.

创建、查看、更新或删除定时任务：一次性提醒、周期任务、后台监控、多轮编辑已有任务、登录态/权限敏感任务。用于用户要求提醒我、稍后检查、持续关注、每天/每周/每小时运行、创建定时任务/提醒/监控、修改/暂停/删除刚才或已有定时任务。

Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.

OpenRouter unified AI API - Access 200+ LLMs through single interface with intelligent routing, streaming, cost optimization, and model fallbacks

Parallel execution engine for high-throughput task completion

Live Upwork market research producing a ranked niche-opportunity dashboard. Use when the user wants to scan the Upwork market, find or validate a freelance niche, asks 'is there demand for X', wants competitor profile analysis, or needs rate observations for a niche. Triggers: 'research my niche', 'scan the Upwork market', 'is there demand', 'what should I specialize in', 'check the market', 'what do freelancers charge for X'.

This skill should be used when the user asks to "create an index", "build a basket of top assets", "buy a weighted basket", "make a portfolio of assets", "equal-weight basket", "rebalance my portfolio", "track the top N tokens", or wants an automated, weighted multi-asset basket that buys in one pass and rebalances on a cadence. Builds the basket spec, delegates each buy and rebalance swap to the swap-integration Trading API flow, and records target weights in state.

Automates multi-source enrichment of IPs, domains, URLs, and file hashes using VirusTotal, AbuseIPDB, Shodan, GreyNoise, URLScan.io, and MISP to provide contextual risk scoring and disposition recommendations for SOC analysts.

Upscale and enhance image and video resolution using AI

Use to recover a day in real time when volume, handle time or availability diverge from plan — reforecasting decisions, break moves, overtime, callbacks and skill flex without burning tomorrow. Trigger for "intraday management", "real-time reforecast", "we are underwater at 11am", move breaks or lunches, call people back in, flex agents between queues, ride out the spike, or when the WFM plan is wrong before close of business.

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

[OMX] Strict autonomous loop: $deep-interview -> $ralplan -> $ultragoal (+ $team if needed) -> $code-review -> $ultraqa

当需要系统性地提升工作专注度和生产力，实现高质量成果时

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

Parallel execution engine for high-throughput task completion

Design and improve product user onboarding (first-time user experience) to drive activation and early retention. Produces an Onboarding & Activation Pack (aha moment spec, first 30 seconds + first mile plan, onboarding journey map, experiment backlog, measurement plan). Use for Growth teams.

**Server Logs:**

Token budget analytics and ROI scoring for AI agent actions. Track token cost per fix, detect wasteful loops, auto-route to fast tier when burn rate is too high. Integrates with token-budget-guard.sh hook. Triggered by /cost-report, "how much did that cost", "token usage", "am I wasting tokens".

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Cancel any active OMC mode (autopilot, ralph, ultrawork, ultraqa, swarm, ultrapilot, pipeline, team)

Ruthless team performance audits (Elon Algorithm) and meeting-to-action extraction. Use for performance audits, meeting action items, or org efficiency reviews.