Behavioural auditor for agentic skills - KTH ASSERT entry-point exercise. n=25 skills, syscall + DNS instrumentation, LLM-derived sandbox-policy prototype, 6-mutation adversarial suite.
npx skills add SirRay03/agentic-skill-behavioral-auditBehavioural auditor for agentic skills - KTH ASSERT entry-point exercise. n=25 skills, syscall + DNS instrumentation, LLM-derived sandbox-policy prototype, 6-mutation adversarial suite.
Source: https://github.com/SirRay03/agentic-skill-behavioral-audit
Discovered by the Awesome Skills daily skill hunter.
多模态 Skill 套件：设计稿转代码/OCR识别/音频摘要/视频剪辑/PPT生成，支持设计稿AI生成前端代码。
Static-analysis scanner for AI-agent configurations (MCP servers, skills, agent permissions). Offline-by-default. SARIF/HTML/JSON output.
Recently updated agent-adjacent repository: stonefruit/Data2Evidence-coding-agent-tools.
Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to
Claude Code plugin that turns a rough software idea into a structured build plan, then guides it through requirements, design, and small working slices using specialized agents.
Design optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection. Use this skill when deciding how many agents to spawn for a task, when choosing between a review team versus a feature team versus a debug team, when selecting the correct subagent_type for each role to ensure agents have the tools they need, when configuring display modes (tmux, iTerm2, in-process) for a CI or local environment, or when building a custom team composition for a non-standard workflow such as a migration or security audit.