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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.
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Delegate code analysis and implementation to Codex CLI without an interactive session. The skill reads ordered output events, extracts the final agent response, and reports errors, with a read-only sandbox used by default.
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Delegate repository analysis and coding tasks to GitHub Copilot CLI without an interactive session. The skill reads structured output, checks errors, and summarizes the final result along with any denied tool requests.
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Find context from past coding sessions in Hindsight long-term memory. Reuse memories already loaded for the session, search for missing details, and reason over accumulated records when answering questions about decisions, project context, or preferences.
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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.
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Hand a scoped coding task to Aider while the coordinating agent reviews changes, runs project checks, and commits the result. Covers task briefs, execution tracking, and follow-up edits, but the executable helper is not bundled.
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Manage coding work from issue intake through implementation, review, deployment, and acceptance checks. Track each completion requirement against fresh evidence, with defined retry limits and explicit escalation when progress needs human input.
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Practice an interview tailored to a specific job, with a chosen format and difficulty. Answer one question at a time, handle follow-up questions, and receive scores and improvement suggestions grounded in your answers.
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Recover hidden malware settings and communication parameters in an isolated CTF environment. Document how values are decoded, preserve supporting evidence, and connect recovered fields to the sample’s observed behavior.
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Analyze packet captures in a CTF sandbox by rebuilding communication sessions and decoding message contents. Recover transferred files and connect packet order, timing, and reconstructed streams to observed host or malware behavior.
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Analyze captured network traffic and binary messages to recover custom protocol structures. The skill organizes message types, fields, and connection states, then produces reproducible decoding steps with supporting evidence for authorized investigations.
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Review Python code for common mistakes in error handling, asynchronous operations, type annotations, and tests. Use a practical checklist and correction examples to guide code reviews, investigate bugs, and improve existing implementations.
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Split multi-step coding, research, or testing into focused assignments for sub-agents, which are agents handling specific parts of a task. The parent agent retains design decisions, integration, and final verification while independent work runs in parallel.
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Retrieve past operational experience from OpenViking before or during coding, configuration, deployment, or recovery work. It reads relevant records, checks whether their assumptions match the current environment, and applies suitable procedures and checks.
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Investigate LLM application failures with Phoenix CLI by reviewing execution records, recording observations, and grouping mistakes into counted categories. Inspect datasets and experiments to identify which failure types deserve evaluation tests first.
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Create a copilot-instructions.md file from an existing codebase. Identify technology versions, architecture, naming conventions, and testing practices, then turn observed patterns into project-specific guidance for GitHub Copilot without introducing unsupported assumptions.
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Generate a customizable AI prompt for finding representative examples in an existing codebase. Configure analysis depth, categories, and snippets so GitHub Copilot can produce exemplars.md with real file references and explanations of coding conventions.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Design, refine, or review web and iOS interfaces using the product’s existing components and visual style. Consult relevant screen examples when useful, then inspect the result for layout problems, inaccessible controls, and broken interactions.
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Examine AI product reliability, learning methods, and model limitations through frameworks drawn from Andrej Karpathy’s public statements. Assess the gap between demonstrations and real use, uneven capabilities, and where people should retain control.
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Unwrap layers of obfuscated PowerShell malware to recover hidden commands, additional malicious code, and server addresses. Combines script structure analysis with execution tracing and decoding tools to support incident investigation and detection work.
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Compose compact, structured prompts for coding, debugging, review, and research with Codex or GPT-5.4. This internal skill defines task scope, completion criteria, output format, verification steps, and evidence requirements using consistent XML tags.
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Turn a project idea into a detailed system plan before coding. Organize architecture, data flows, dependencies, and file-level tasks in a linked Markdown workspace, with research references, consistency checks, and saved state for resuming later.
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Guides large language model reinforcement learning with miles, covering environment setup, low-precision training, consistency between training and inference, and speculative decoding, where a smaller model proposes tokens for a larger model to verify.
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