Coding standards, frameworks, refactoring, and code review (16.9K skills)
Plan SDK behavior changes by defining required outcomes, compatibility boundaries, and unsupported cases. Reuse existing implementation paths, assess review feedback, and reconsider designs when repeated fixes introduce complexity beyond the original requirement.
Assess GitHub issues and pull requests by checking demonstrated user needs, existing alternatives, compatibility, and maintenance costs. Produce an evidence-based maintainer recommendation through code and document inspection, without running tests or examples.
Fix a small formatting bug in a credit note shell script while keeping the output label as credit and the amount positive. Run the specified targeted test and summarize the bug, fix, and verification command.
Prepare an English pull request title, description, and branch suggestion from completed local changes. It reviews Git changes, includes untracked files, and formats issue references so the draft is ready to paste into GitHub.
Use the GitHub command-line tool to inspect issues, pull requests, and automated workflow runs. Check failed steps and logs, retrieve additional details through the API, and extract selected fields into structured results.
Turn repeated workflows into reusable Picoclaw skills, or update and review existing ones. Organize SKILL.md instructions, scripts, reference documents, and output assets, then check the structure and test representative tasks.
Read and control sensors, displays, and other peripherals on Sipeed boards through I2C and SPI, two hardware communication interfaces. Find connected devices, prepare shared pins, and troubleshoot wiring, permissions, and communication settings.
Control interactive command-line programs through tmux by sending keystrokes, reading terminal output, and waiting for prompts. Use separate sessions to operate Python consoles or run multiple coding agents while checking their progress and results.
Set up, debug, and extend PicoClaw using its own commands and configuration structure. Get guidance on model authentication, external tool connections, scheduled tasks, and how conversations are routed and stored.
Retire a FastGPT workflow node while preserving existing workflows. The skill guides changes to templates, execution handlers, and interface references so the node disappears from creation menus but still loads, runs, and displays a replacement notice.
Develop and review FastGPT data migration tasks for automatic system upgrades. Define safe reruns, resume points, progress reporting, and failure handling, while checking task order and whether upgrades must block application startup.
Integrate new FastGPT resources, such as AgentSkill or Plugin, with permission management. Choose an integration guide based on resource hierarchy and permission inheritance, locate the relevant code, and review a checklist for missing implementation steps.
Translate selected FastGPT interface text files from Simplified Chinese into every supported target locale. Check product terminology and interface context, preserve JSON structure and placeholders, and validate the translated files for consistency.
Develop and review FastGPT APIs with consistent input and output checks, TypeScript types, and OpenAPI documentation. It guides the use of Zod schemas, definitions that describe and validate data, alongside permission checks and reusable structures.
Explain how agentmemory stores and retrieves coding agents’ memories, including its engine, search methods, memory lifecycle, ports, and web viewer. Useful for understanding the system or planning extensions to its functions.
Connect agentmemory to coding agents such as Claude Code and Codex while preserving existing server settings. It guides configuration, host restarts, and checks that memory tools are available and can save and retrieve information.
Trace a file, function, or line through Git history to the agent session linked to its commit. It presents recorded commit details, session summaries, and important observations to help explain the change.
List Git commits linked to agent work sessions, with branch or repository filters. See each commit’s message, date, linked sessions, and observation counts to review recorded changes alongside their session context.
Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.
Create, update, or review agentmemory skills using a shared format. It guides document structure, supporting files, and generated reference data so contributions follow consistent rules and stay aligned with the source code.
Helps agents choose the right agentmemory tool through MCP, a protocol for connecting agents to tools. It explains tool roles and points to parameter references for saving, retrieving, organizing, and maintaining stored knowledge.
Evaluate a proposed software change before implementation. It examines project files and official sources, compares options and trade-offs, and builds a concrete plan covering affected systems, effort, risks, and unresolved questions for the user's approval.
Submit existing local changes as a pull request by reviewing the diff, running project checks, preparing a branch and commit, and pushing to GitHub. It follows contribution rules and preserves template declarations that require human verification.
Update a project's changelog using GitHub releases, git history, and code differences. Select changes that matter to users, match the existing format, and write concise entries for the requested release.