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Found 3,215 Skills
Maintain /do routing tables and command references when skills or agents are added, modified, or removed. Use when skill/agent metadata changes, after skill-creator-engineer or agent-creator-engineer runs, or when routing tables need synchronization. Use for "update routes", "sync routing", "routing table", or "refresh /do". Do NOT use for creating new skills/agents, modifying skill logic, or manual /do table edits.
Spawn 10 independent parallel agents to analyze source material from distinct perspectives, synthesize findings, and apply improvements to a target agent or skill. Use when source material is complex and multi-angle extraction justifies 3-5x token cost over inline analysis. Use for "parallel analysis", "multi-perspective", or "deep extraction". Do NOT use for routine improvements, simple source material, or when token budget is limited.
Mechanize Pattern 15 — the seven-pass adversarial review protocol for academic manuscripts. Spawns 7 forked subagents in parallel (abstract, intro, methods, results, robustness, prose, citations), then synthesizes a prioritized revision checklist. Use for submission-ready or R&R-stage papers where single-pass review isn't enough.
Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when user says "优化技能", "meta optimize", "improve skills", "分析使用记录", or wants to optimize ARIS's own harness components based on accumulated experience.
AI-powered web search via Exa with content extraction. Use when user says "exa search", "web search with content", "find similar pages", or needs broad web results beyond academic databases (arXiv, Semantic Scholar).
Run a formal, multi-dimensional code review of a pull request. Reads the PR diff, classifies change types, dispatches parallel reviewers by dimension (correctness, consistency, docs-sync, plus conditional security/edge-cases/UX/performance/structure/maintainability), and synthesizes findings into an actionable punch list. Use when the user asks to review a PR, run /deep-review, mark a PR as ready for review, or requests a formal/thorough code review.
Python video composition with moviepy 2.x — overlaying deterministic text on AI-generated video (LTX-2, SadTalker), compositing clips, single-file build.py video projects. Use when adding labels/captions/lower-thirds to LTX-2 or SadTalker outputs, building short ad-style spots in pure Python without Remotion, or doing programmatic video composition. Triggers include text overlay on video, label LTX-2 clip, caption SadTalker output, lower third, build.py video, moviepy, Python video composition, sub-30s ad spot.
E2E testing for Windows native desktop apps (WPF, WinForms, Win32/MFC, Qt) using pywinauto and Windows UI Automation.
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
Transcribe audio with StepFun's stepaudio-2.5-asr — an SSE endpoint (NOT /v1/audio/transcriptions) with 32K context, ~85-101x RTF on long audio, and a single-call ceiling around 30 minutes (no client-side chunking). Use when transcribing Chinese / English audio with StepFun, when long-form recordings (5-30 min) need to land in one request, when migrating from step-asr / step-asr-1.1, or when hitting the misleading `model stepaudio-2.5-asr not supported` error (which actually means wrong endpoint). Triggers on 阶跃 ASR, StepFun ASR, stepaudio-2.5-asr, 转录, 语音识别, 长音频转写, 语音转文字. For TTS with the sibling stepaudio-2.5-tts model, use the stepfun-tts skill instead.
Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.
Generate engine-specific test helper libraries for the project's test suite. Reads existing test patterns and produces tests/helpers/ with assertion utilities, factory functions, and mock objects tailored to the project's systems. Reduces boilerplate in new test files.