100+ agent skills

Multi-bot, multi-chat routing. Forward, mute, and manage grouped DMs. The reference Telegram skill for power users.

Read-only by default. Drafts replies, surfaces important threads, ignores newsletters. Understands priority from context.

Watches PRs across your repos, posts review summaries, drafts changelogs, and flags risky migrations.

Drops a summary comment on every PR, flags risky migrations, and suggests one concrete test to add.

Summarises thread noise, surfaces urgent mentions, and drafts channel updates. Works across multiple workspaces.

Move tickets across columns by chatting. Adds time tracking, auto-links commits to issues, sends standup summaries.

Query, update and chart your spreadsheets by chat. Paste in CSV and ask questions — no formulas needed.

Fetch any URL and get clean Markdown. Handles JS-rendered pages, paywalls, and infinite scroll.

Moderate messages, greet new members, summarise hot threads, and schedule announcements across servers.

Two-way sync. Write meeting notes, read project docs, search across all databases in one query.

Create issues, manage sprint boards, and generate velocity reports through conversational commands.

Parses incoming invoices, reconciles charges, alerts on failed payments, and generates revenue summaries.

Adds, completes, and re-prioritises tasks. Weekly review prompts and inbox zero flows baked in.

Run read-only SQL queries against your Postgres database using plain English. Returns formatted tables.

Log calls, update deal stages, enrich contacts from LinkedIn, and draft follow-up emails — all by chat.

Trigger deployments, check CloudWatch logs, manage EC2 instances, and get cost alerts from a chat interface.

Trigger any Zapier zap from chat. Connect thousands of apps without writing integration code.

Read-only secrets retrieval. Server-side decryption — credentials are never sent to the LLM in plaintext.

Read and write Airtable bases by chat. Great for ops teams who live in Airtable and want AI-driven updates.

Auto-prep notes for every meeting, batch-cancel low-priority blocks, suggest reschedules when conflicts arise.

Transcribes and summarises calls via a Twilio number. Files summaries under the right contact automatically.

Draft support replies, tag conversations, escalate VIPs, and summarise open ticket backlog.

Query orders, process refunds, update inventory, and draft customer reply emails for your Shopify store.

Draft, schedule, and analyse tweets. Thread composer with optimal timing recommendations built in.

Get error digests, assign issues to teammates, and ask why something spiked in plain English.

Daily traffic summaries, anomaly alerts, and natural-language queries over your GA4 property data.

Query deals, log activities, update opportunity stages, and get weekly pipeline health reports.

Extract design tokens, comment on frames, and generate component documentation from your Figma files.

Draft and schedule LinkedIn posts, monitor engagement, and repurpose long-form content into short posts.

Query user events, build funnel reports, and get retention cohort summaries through plain-English questions.

Create and update Webflow CMS items by chat. Great for content teams who want to publish fast.

Parse Typeform responses, route to the right team, and generate summaries of survey results.

Monitor subreddits for mentions, trends, and competitor activity. Get daily digests or real-time alerts.

Deep dive on a topic with a falsifiable thesis, cited claims, and explicit uncertainty

description: Design tools that agents can use effectively, including when to reduce tool complexity. Use when creating, optimizing, or reducing agent tool sets.

Pick the highest-★ dormant watched repo and make one targeted improvement to reactivate it — refresh stale model references, README, or metadata

Draft a Show HN post (plus shorter Reddit r/MachineLearning + r/selfhosted variants) from the live repo state — README, SHOWCASE, recent repo-articles + project-lens, real autonomous behavior examples from logs, and current stars/forks/skill counts. Operator pastes; agent writes.

Tool use patterns for Claude including schema design, tool_choice modes, result handling, parallel execution, error recovery, and extended thinking integration.

CI/CD reference for Megatron Bridge — pipeline structure, commit and PR workflow, CI failure investigation, and common failure patterns.

Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.

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Dev environment setup for Megatron Bridge — container-based development, uv package management, lockfile regeneration, adding dependencies, Slurm container usage, and common build pitfalls.

Guide for adding support for new LLM or VLM models in Megatron-Bridge. Covers bridge, provider, recipe, tests, docs, and examples.

Use when writing DALI data loading or preprocessing code with `nvidia.dali.experimental.dynamic` (ndd), or when converting DALI pipeline-mode code to dynamic mode, or when the user asks about DALI dynamic mode, imperative DALI, or ndd. Use this skill any time someone mentions 'ndd', 'dynamic mode', or wants to load/augment data with DALI outside of a pipeline definition.

Find and rank GitHub developers by location, technology, and role. Search for candidates, get scored profiles with tech stack matches, activity, and contact info.

name: tool-selection-framework

Convert single-node scripts to multi-node Slurm sbatch jobs and debug common multi-node failures. Covers srun-native vs uv run torch.distributed approaches, container setup, NCCL timeouts, OOM sizing for MoE models, and interactive allocation.

Validate and use selective and full activation recompute in Megatron Bridge to reduce GPU memory usage at the cost of extra compute.

External NeMo-RL end-to-end validation workflow for Megatron-Bridge model/provider changes, including downstream compatibility checks, external RL lifecycle behavior, Megatron policy setup, HF import/export, checkpoint/resume, non-colocated vLLM refit, delta weight transfer, optional LoRA/generation variants, and questions such as "does this model work in NeMo-RL", "run NeMo-RL e2e", or "external RL loop validation". Covers running NeMo-RL Megatron policy jobs from a Bridge checkout, choosing GR

Operational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.

MoE expert-parallel communication overlap in Megatron Bridge. Covers dispatch/combine overlap, flex dispatcher backends, and expert wgrad scheduling.

Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM fixes.

Validate and use CPU offloading in Megatron Bridge, including layer-level activation offloading and fractional optimizer state offloading with HybridDeviceOptimizer.

Operational guide for enabling hierarchical context parallelism in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.

Fetch ~30 older tweets, pre-filter for remixability, then produce 10 new rephrased versions across diverse strategies with post-write quality gates

Semantic tool search with embeddings for scalable tool discovery. Enables on-demand tool loading to reduce context usage by 90%+ for large tool libraries.

Fleet-level skill-run analytics — ranks skills by 7d run count, surfaces success rates, exit-taxonomy distribution, and anomaly flags (significance-gated)

Recommend and customize Megatron Bridge recipes for a user's model, GPU count, and training goal. Indexes library recipes (pretrain/SFT/PEFT) and performance recipes.

Long-context MoE training guidance for Megatron Bridge. Covers CP sizing, selective recompute, dispatcher choices, and practical patterns from DSV3, Qwen3, and Qwen3-Next long-context experiments.

Operational guide for enabling TP, DP, and PP communication overlap in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.

Operational guide for choosing and combining parallelism strategies in Megatron Bridge, including sizing rules, hardware topology mapping, and combined parallelism configuration.

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Create a six-frame storyboard that shows a user's journey from problem to solution. Use when you need a fast narrative for alignment, concept reviews, or demos.

External verl end-to-end validation workflow for Megatron-Bridge model/provider changes. Covers running a small verl Megatron backend job from a Bridge checkout, choosing LoRA/DDP plus optional save/resume and parallelism variants, setting PYTHONPATH so verl imports the local Bridge tree, and reporting pass/fail evidence.

Testing reference for Megatron Bridge — unit and functional test layout, tier semantics (L0/L1/L2/flaky), script conventions, running tests locally, adding/moving/disabling tests, and pytest conventions.

Thesis-driven article about a watched repo — falsifiable claim, cited evidence, self-edit quality gate

CLI-first tool selection policy for Claude Code. Use when choosing between CLI tools and MCP servers, designing new agents, or reviewing agent tool configurations. Do NOT use for executing commands or running tools -- this is for tool selection decisions during agent/config design only.

Friendly onboarding when users ask about capabilities

Obsidian-first SDD workflow for complex work, feature tickets, task state, and multi-session handoffs under `canon/<project>/...`. Use this skill to drive one active canon task note per session and keep feature/task history in Obsidian instead of local scratch files.

Domain knowledge for the nightly main-to-dev sync workflow. Covers merge strategy, CI architecture, failure investigation, and known issues.

Research and draft a response to a GitHub issue or question from an external contributor.

Onboard 1-node GitHub MR functional tests for GB200 from existing mr-scoped 2-node tests.

Refresh golden values from a GitHub Actions workflow run (failing-only or all jobs), score the change with average normalized relative differences, and produce a PR-ready summary. Use when the user asks to update goldens for a CI run, refresh golden values from a workflow ID, or generate a golden-value diff summary for a PR description.

Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.

Chat-based AWS infrastructure assistance using AWS CLI and console context. Use for querying, auditing, and monitoring AWS resources (EC2, S3, IAM, Lambda, ECS/EKS, RDS, CloudWatch, billing, etc.), and for proposing safe changes with explicit confirmation before any write/destructive action.

Bump the NVIDIA PyTorch base image (`nvcr.io/nvidia/pytorch:<YY.MM>-py3`) used by Megatron-LM CI. Covers the two pin sites (GitHub CI in `docker/.ngc_version.dev` and GitLab CI in `.gitlab/stages/01.build.yml`), the post-bump CI loop (re-run functional tests, refresh golden values, mark broken tests), and the gotchas that bit PRs #4611 and #4688.

Combined briefing — token movers, tweet roundup, paper pick, GitHub issues, and HN digest in one run

Lead with confirmed exploitation (CISA KEV), enrich with EPSS, filter GitHub Advisories to your tracked stack, output one action per item

Apply for go-servemux-rest-api-cursorrules-prompt-file. --- description: This rule emphasizes security, scalability, and maintainability best practices in Go API development. globs: /*/**/*_api.go

Probe of repos on the security watchlist — check if private vulnerability reporting has been enabled, notify when status flips, re-submit any queued advisories or flag for re-research when draft was lost

Evaluates accuracy of quantized or unquantized LLMs using NeMo Evaluator Launcher (NEL). Triggers on "evaluate model", "benchmark accuracy", "run MMLU", "evaluate quantized model", "accuracy drop", "run nel". Handles deployment, config generation, and evaluation execution. Not for quantizing models (use ptq) or deploying/serving models (use deployment).

Query and browse evaluation results stored in MLflow. Use when the user wants to look up runs by invocation ID, compare metrics across models, fetch artifacts (configs, logs, results), or set up the MLflow MCP server. ALWAYS triggers on mentions of MLflow, experiment results, run comparison, invocation IDs in the context of results, or MLflow MCP setup.

Serve a quantized or unquantized LLM checkpoint as an OpenAI-compatible API endpoint using vLLM, SGLang, or TRT-LLM. Use when user says "deploy model", "serve model", "start vLLM server", "launch SGLang", "TRT-LLM deploy", "AutoDeploy", "benchmark throughput", "serve checkpoint", or needs an inference endpoint from a HuggingFace or ModelOpt-quantized checkpoint. Do NOT use for quantizing models (use ptq) or evaluating accuracy (use evaluation).

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Monitor submitted jobs (PTQ, evaluation, deployment) on SLURM clusters. Use when the user asks "check job status", "is my job done", "monitor my evaluation", "what's the status of the PTQ", "check on job <slurm_job_id>", or after any skill submits a long-running job. Also triggers on "nel status", "squeue", or any request to check progress of a previously submitted job.

Generate an Atom XML feed from articles, validate it, and notify only when it actually changes

Apply for go-backend-scalability-cursorrules-prompt-file. --- description: General rule for backend development expertise across the project. globs: **/*

Ensures commits follow conventional commits, branch naming conventions, and PR templates. Use when creating commits, branches, or PRs, or when user mentions git workflow.

Integrate Vercel AI SDK for LLMs, Chatbots, Generative UI, and Agentic Workflows.

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Expert email management assistant for Apple Mail. Use this when the user mentions inbox management, email organization, email triage, inbox zero, organizing emails, managing mail folders, email productivity, checking emails, or email workflow optimization. Provides intelligent workflows and best practices for efficient email handling.

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Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.

Accountability check on a configured set of tracker skills. Verifies each tracker is producing citable signals in articles/newsletters. Surfaces uncited trackers so the operator can demote or kill them.

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