206 skills · sorted by relevance
Search local session histories across Codex, Claude Code, OpenCode, and other coding agents. Find earlier requests, inspect transcripts and child sessions, and reconstruct past work using recorded evidence, with filters for dates, projects, platforms, and models.
Find, generate, and prepare media for HyperFrames projects, saving assets locally with records for reuse. Covers images, music, voiceovers, transcription, captions, background removal, media edits, and visual treatments such as color correction or retro styling.
Run protein structure prediction, molecular design, and docking tools on Tamarind Bio without a local GPU. Guides tool selection, input validation, job submission, batch processing, and result retrieval through its REST API or MCP server.
Set up and customize Pi, a terminal coding agent framework. This skill guides model configuration, extension development, terminal interfaces, and integration with other applications through its SDK, a software development kit, or process messaging.
Simulate quantum dynamics, steady states, and spectra with QuTiP 5. The skill guides solver selection and checks physical assumptions, units, state validity, and numerical convergence so local simulation results can be reviewed with their limitations.
Search Apple Notes by meaning or exact text, discover related notes and unexpected connections, and synthesize ideas with citations. The skill guides local setup and tool selection, with on-device search and optional local or cloud language models for synthesis.
Build and debug Apify Actors, cloud programs for web scraping, automation, and data processing. Get guidance on language templates, input and output schemas, runtime code, local testing, and deployment, with practices for handling credentials and external data.
Analyze bond prices, yields, and issuers’ ability to repay debt. The skill covers interest rate exposure, default risk models, yield spreads, Chinese local government financing platform bonds, and securities backed by pools of loans.
Convert language models to GGUF and reduce their size through quantization, which stores model weights at lower precision. Guides cover compression choices, local inference on CPUs and Apple Silicon, and integration with tools such as Ollama.
Check today's AI coding costs and token usage from local session logs with CodeBurn. Get a short summary of total spending, the most expensive models and projects, unusual usage, and one concrete suggestion for reducing costs.
Test Omnigent’s Cursor SDK integration against a live local server. Build test agents, run real conversations, and check authentication, model selection, and tool connections while investigating empty responses or bridge processes left after shutdown.
Use extracted document content, design evidence, and local assets in iPolloWork video, slide, website, or design templates. Apply confirmed requirements and verify that supplied assets actually appear in the output, without using models to reparse references.
Check AltLLM Portal credit, expiry dates, billing transactions, and usage through the local altllm CLI. Review activity by period, model, or API key, and redeem promo codes using a saved Portal session.
Investigate a Codex CLI session by matching its local conversation record with production router logs. Use the session ID to examine missing reasoning summaries, routing markers, unexpected models, or unusual tool calls and trace relevant code paths.
Transcribe audio files locally with the Whisper command-line tool, without an API key. Export text or translated subtitles, and choose smaller or larger models to balance processing speed and transcription accuracy.
Search local session histories across Codex, Claude Code, OpenCode, and other coding agents. Find earlier requests, inspect transcripts and child sessions, and reconstruct past work using recorded evidence, with filters for dates, projects, platforms, and models.
Explain an existing machine learning model by summarizing influential input features and examining individual predictions. It helps investigate unexpected feature interactions and communicate model behavior to nontechnical stakeholders, while noting limitations and potentially misleading explanations.
Fine-tune a pretrained KERMT model on a CSV of molecular structures and labeled targets. The workflow checks inputs, prepares features, launches training in a container, and saves trained models, logs, and test results.
Audits, diffs, copies, and lists providers/models, adds models, and switches the default model in local openclaw.json configs; diagnoses gateway/plugin failures (down, parked, broken, or out of date after an upgrade). Use for 虾/龙虾 config audits. Not for model-error repair (use openclaw-model-switch).
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Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when exporting Custom Vision models, calling prediction APIs, using ONNX/TensorFlow, managing CMK/RBAC, or Smart Labeler, and other Azure AI Custom Vision related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Foundry Local (use microsoft-foundry-local).
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Implement local persistence with SwiftData, Core Data, and secure storage. Use when setting up SwiftData models, Core Data stacks, or local persistence in iOS.
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Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.
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Find and compare recommended Hugging Face models for a task using benchmarks, model size, and device constraints. Use for model selection questions; use huggingface-local-models for GGUF setup and hf-cli for Hub operations.
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Manual QA harness for the senpi coding agent itself. MUST USE after changing packages/ai, packages/agent, packages/coding-agent, or packages/tui — a green typecheck and `npm test` are NOT QA. Drives the real CLI from source in an isolated sandbox (never touches ~/.senpi or real credentials) across four channels: remote RPC (--mode rpc JSONL stdio), TUI smoke (node-pty on Windows, tmux on POSIX), mock loop (a local fake model server for deterministic, zero-token agent-loop runs), and CLI smoke (--help/--print/--list-models). Every helper ships a --self-test. Use whenever someone says qa senpi, test the agent, verify my change, rpc qa, tui qa, mock-loop qa, smoke the cli, or needs evidence that an agent-loop, tool, keybinding, or provider change works end to end. Capture evidence to local-ignore/qa-evidence/.
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