2.8K skills · sorted by relevance
Configure browser startup with a visible or hidden window, and optionally open a local debugging port for another tool to connect. The skill explains launch parameters, compatibility behavior, and when a browser restart is required.
Troubleshoot Zoom integration failures across authentication, API requests, event notifications, and SDK behavior. Get likely causes ranked by probability, relevant reference links, targeted fix steps, and a short checklist to verify the result.
Investigate errors and unexpected behavior through reproduction, isolation, diagnosis, and a proposed fix. Receive a structured report covering the root cause, necessary code or configuration changes, and suggested tests to prevent the issue from returning.
Create, update, and debug Docker-based end-to-end tests for the Composio CLI. Covers running the executable, keeping test data separate, checking command output, and maintaining package manifests within the CLI test suite.
Build, edit, or debug backend AI agents with eve, a framework that represents agents as directories of files. Work on instructions, tools, connections, schedules, and related components using documentation bundled with the installed version.
Investigate difficult bugs by adding temporary logs to the actual execution path and reproducing the reported behavior. Analyze JSONL logs, which store one structured event per line, then fix the cause, verify regression tests, and remove debugging artifacts.
Extract fields, filter records, and reshape JSON from API responses, configuration files, or logs using Crush’s built-in jq. Get help writing and debugging transformations, constructing new JSON, and formatting output for other commands.
Investigate difficult bugs through explicit hypotheses, targeted logs, and repeated checks against actual data. Keep an investigation journal to track findings, examine environment differences and leftover state, and confirm the root cause before applying a fix.
Turns recurring workflows and proven debugging solutions into reusable skill packages. It creates SKILL.md, a readable overview, and optional supporting examples from a user description or saved project memory, with checks for completeness and portability.
Build, run, and debug the Kilo JetBrains plugin using its Gradle workflows. It covers isolated development storage, chat logs, sandbox recovery, and switching between a pinned CLI release and locally built CLI code.
Implement and debug Google OAuth 2.0 refresh tokens bound to a client key. Covers key generation, signed DPoP proofs that demonstrate key possession, and nonce challenge retries in WebCrypto and JavaScript environments.
Write and debug code for further training large language models with TRL. Match training methods to dataset formats, configure supervised or preference-based training, and set up reward functions through Python or the command line.
Debug json-render interfaces with an inspector panel that shows screen specifications, editable runtime state, action history, and streamed updates. Select a rendered page element to locate its definition and investigate display or interaction problems.
Develop and debug LangBot's backend and web frontend. The skill guides environment setup, API additions, authentication, database migrations, and testing, including updates to matching MCP tools so agents can use changed API features.
Build and debug LangBot plugins that handle messages, commands, and AI tool calls. The skill covers SDK usage, common errors, test environment setup, WebSocket message testing, and preparation for publishing to LangBot Space.
Test and debug REST and GraphQL APIs using curl, httpie, Postman collections, or scripted tests. Check authentication, invalid inputs, pagination, and response details to identify failures that a successful status code alone may miss.
Analyze records of an AI agent’s decisions and tool use to find repeated failures, lost goals, and misunderstood instructions. Use the findings to refine prompts, rerun tasks, and turn debugging lessons into reusable skills.
Investigate software errors, version conflicts, and API questions across official documentation, GitHub, technical Q&A, and Chinese developer communities. Results distinguish matching errors, source authority, and reported environments, giving you documented leads and next checks for debugging.
Diagnose unreachable or unhealthy OpenShell gateways and sandbox startup failures. Identify the underlying execution platform, then examine logs, authentication, certificates, and configuration with the matching tools to narrow down the cause.
Diagnose failed model requests from OpenShell sandboxes to hosted APIs or local servers such as Ollama and vLLM. Check provider attachment, access rules, credentials, network layout, and client settings to identify the narrowest configuration change needed.
Find, add, and combine shadcn/ui components to build forms, dashboards, and other interfaces. Use project settings and component documentation to guide styling, debugging, preset changes, and updates that preserve local modifications.
Create, migrate, refine, or debug CARLA vehicle assets with Blender and Unreal. Use real vehicle references to guide geometry and materials, configure wheels, lights, and physics, and deliver editable sources with evidence from runtime validation.
Validate CARLA pedestrian navigation by sampling walkable locations and reporting their coverage. Draw the samples as debug points to inspect the walkable area after a map import or investigate pedestrians that will not move.
Guides PyTorch model training and fine-tuning, from choosing architectures to configuring optimizers and learning rates. Provides troubleshooting steps for unstable loss and memory shortages, plus methods for improving GPU throughput and comparing experiments.