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Found 43 Skills
Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files.
Generate a self-contained HTML viewer for any Claude Code session, including agent team sessions with full inter-agent DM timelines. Use whenever the user asks to "view a session", "visualize a conversation", "show me what happened in session X", "generate a session viewer", "replay a session", or references viewing/inspecting Claude Code JSONL logs. Also use when the user provides a session ID and wants to see the conversation.
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.
Use when diagnosing unexpected behavior, failed workflows, bugs, browser or Node.js runtime issues, logs, traces, or when preparing a root-cause hypothesis. 诊断异常、定位 bug、判断修复方向时使用：先建立证据表，区分运行时事实和代码推断，避免多层猜测；证据不足时添加 copy-friendly 浏览器日志或本地 Node.js JSONL 日志。
Use when debugging a Nemo Gym run or reward profiling job. Covers rollout collection failures, empty or partial JSONL outputs, stale materialized inputs, verifier/schema errors, Ray or Slurm issues, vLLM readiness, judge failures, tool/sandbox failures, cache problems, and throughput bottlenecks.
Auto-capture per-session token usage from the Claude Code session jsonl and persist to the cost-tracking namespace
Local token cost analytics dashboard for Claude Code sessions — reads JSONL transcripts and provides per-prompt cost breakdowns, heatmaps, and usage insights.
Building & extending Pi — authoring TypeScript extensions (ExtensionAPI, registerTool, registerProvider, /commands, UI hooks), publishing as npm/git packages (pi-package), embedding via JSON-RPC mode (--mode rpc/json, JSONL framing, AgentSession SDK), and developing inside the pi_agent_rust repo. Use for any "how do I build a Pi extension/package/SDK client" question.
Turn a brief music description and optional tagged lyrics into a professional MiniMax Music 3 structured caption with Global Metadata, Vocal Details, and a section-aware Arrangement. Use when users ask to enhance a music-generation prompt, preserve lyric-section directives, retrieve a similar style from bundled templates, fuse styles, or produce JSON or JSONL caption output.
Use to help users get started with Nemo Gym reward profiling. Covers the basic ng_run, ng_collect_rollouts, and ng_reward_profile workflow, repeated rollouts, materialized inputs, rollout JSONL artifacts, task and rollout identity, output inspection, partial profiling, and rollout_infos. For failed jobs, prefer nemo-gym-debugging.
Manage local Codex session transcripts, including listing candidate sessions, exporting full or selected sessions to organized Markdown, inspecting archived sessions, and summarizing tool-call history. Use when the user asks to scan, parse, archive, inspect, recover, summarize, manage, or convert Codex sessions, `~/.codex/sessions` data, `~/.codex/archived_sessions` data, `.jsonl` transcripts, tool-call history, or hard-to-read Codex conversation logs.
Archive deployment records with merged common+environment config context (including remote port) for Makefile-first deployment workflow.