Total 50,615 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Router skill for LLMQuant hedge-fund and PM strategy workflows. Use when the user needs equity long/short, long-biased, event-driven, macro, quant, or multi-strategy playbooks.
Router skill for LLMQuant portfolio workflows. Use when the user needs company profiles, thesis tracking, theme research, watchlist monitoring, or alert management.
Use when an agent needs to operate the user's real Chrome session — listing tabs, reading the page, clicking, filling, typing into rich editors, pressing keys, evaluating JS, capturing screenshots, and reading console/network buffers. All actions go through CDP and run on backgrounded tabs without stealing focus.
Audits AI-implemented work for honest completion. Runs independent-evaluator checks against task artifacts, transcripts, tests, CI evidence, requirement-to-test mapping, status front matter, and quality gates; flags skipped tests, weakened assertions, mock-only confidence, snapshot drift, happy-path-only coverage, flaky retries, and status/evidence mismatches. Use when validating completed Compozy tasks, AI-authored PRs, or codex-loop iterations. Do not use for real-user QA, persona/journey testing, exploratory charters, or product usability sessions; use qa-execution for those.
Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.
Find the right Deepgram documentation for any task. Use whenever someone needs help locating docs, understanding which API to use, or wants to ask questions about Deepgram. Covers all product areas: speech-to-text, text-to-speech, voice agents, audio intelligence, and self-hosted deployments.
Install Holoscan SDK natively on Ubuntu via apt. Use for C++ installs on Ubuntu; pair with /holoscan-install-wheel for Python.
Capability discovery and current-state verification for Heavy Path, ambiguous repo/runtime ownership, and runtime-dependent Standard Path work.
Hand off the current task to the SLICC browser agent, or install a new skill into SLICC from a GitHub repo. Use this skill when the user says things like "handoff to slicc", "move this to slicc", "move to the browser", "test in the browser", "handoff to browser", "install this skill in slicc", "upskill slicc with this repo", "add this skill to slicc", or otherwise asks you to continue the work inside the SLICC browser agent.
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
Automated factory that converts GitHub repositories into standardized AI Skills. This tool is used when users provide a GitHub URL and want to "package", "wrap", or "create a Skill". It supports automatic retrieval of repository metadata, generation of standard directory structures, and injection of extended metadata required for lifecycle management.
Helps users discover and install capabilities from the open agent skills ecosystem. Use when users ask "how do I do X" for specialized tasks, request "find a skill for X", want to extend agent capabilities, or need help with specific domains (testing, design, deployment, etc.).