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Found 14 Skills
API integration patterns for autonomous-dev including subprocess safety, GitHub CLI integration, retry logic, authentication, rate limiting, and timeout handling. Use when integrating external APIs or CLI tools.
Subprocess and concurrency discipline for Python: how to run external programs safely, and how to pick the right concurrency model instead of the habitual one. Use when spawning processes with subprocess or asyncio subprocesses, writing threading or ThreadPoolExecutor code, using multiprocessing or ProcessPoolExecutor, sizing worker pools, bounding fan-out, or diagnosing deadlocks, hangs, orphaned children, and zombie processes. Covers argv vs shell, timeouts that kill the whole process tree, pipe deadlocks, start methods (spawn/forkserver/fork), pickling limits, GIL and free-threading, and cancellation. For event-loop and coroutine rules (TaskGroup, blocking calls, cancellation), use python-async-best-practices instead.
Security audit and vulnerability scanning for AI agent skills before installation. Detects prompt injection in SKILL.md files, dangerous code patterns (eval, exec, subprocess), network exfiltration, credential harvesting, dependency supply chain risks, file system boundary violations, and obfuscation. Produces PASS/WARN/FAIL verdicts with remediation guidance. Use when evaluating untrusted skills, pre-install security gates, or auditing skill repositories.
Use before writing or editing any Python code — scripts, functions, bug fixes, cron jobs, data-processing one-offs, or additions to an existing .py file — even if the request sounds quick, casual, or "just a simple script." Applies whether the user names a .py file, describes what the script should do, or asks you to add/fix a function in Python. Covers required standards: type hints, no global variables, logging instead of print, wrapping any I/O (HTTP, DB, subprocess, file) in try/except, commenting the why not the what, writing a real test, and where to place design docs. Does not apply to conceptual Python questions with no code to write (e.g. explaining language features, comparing list vs tuple, explaining what an existing traceback means when the user hasn't asked for a fix, package install help, or learning-resource recommendations), and does not apply to non-Python languages.
Delegate a sub-task to Claude Code via the Agent Client Protocol (ACP). Use this skill whenever you want to hand off work to Claude — complex agentic coding with MCP tool access, detailed multi-file refactors, tasks requiring Claude's reasoning style, or anything where Claude's strengths give an advantage. Also invoke when the user asks you to "ask Claude", "use Claude for this", or "run this through Claude". The script handles subprocess lifecycle and ACP session setup; you just provide the prompt and read stdout.
Reference: review of SaaS subscription agreements with attention to the terms that matter most in subscription deals — auto-renewal mechanics, price escalation, data portability, uptime SLAs, and subprocessor rights. Loaded by /commercial-legal:review when a SaaS or subscription agreement is detected.
Security audit and vulnerability scanner for AI agent skills before installation. Use when: (1) evaluating a skill from an untrusted source, (2) auditing a skill directory or git repo URL for malicious code, (3) pre-install security gate for Claude Code plugins, OpenClaw skills, or Codex skills, (4) scanning Python scripts for dangerous patterns like os.system, eval, subprocess, network exfiltration, (5) detecting prompt injection in SKILL.md files, (6) checking dependency supply chain risks, (7) verifying file system access stays within skill boundaries. Triggers: "audit this skill", "is this skill safe", "scan skill for security", "check skill before install", "skill security check", "skill vulnerability scan".
Delegate a sub-task to Gemini CLI via the Agent Client Protocol (ACP). Use this skill whenever you want to hand off work to Gemini — large-context summarization, Google Search grounding, tasks that exceed Claude's context window, or anything where Gemini's 1M-token window or real-time search gives an advantage. Also invoke when the user asks you to "ask Gemini", "check with Gemini", or "run this through Gemini". The script handles subprocess lifecycle and ACP session setup; you just provide the prompt and read stdout.
Implements security chaos engineering experiments that deliberately disable or degrade security controls to verify detection and response capabilities. Tests WAF bypass, firewall rule removal, log pipeline disruption, and EDR disablement scenarios using boto3 and subprocess. Use when validating SOC detection coverage and resilience.
Build software products autonomously via GSD headless mode. Handles the full lifecycle: write a spec, launch a build, poll for completion, handle blockers, track costs, and verify the result. Use when asked to "build something", "create a project", "run gsd", "check build status", or any task that requires autonomous software development via subprocess.
Complete FFmpeg + OpenCV + Python integration guide for video processing pipelines. PROACTIVELY activate for: (1) FFmpeg to OpenCV frame handoff, (2) cv2.VideoCapture vs ffmpeg subprocess, (3) BGR/RGB color format conversion gotchas, (4) Frame dimension order img[y,x] vs img[x,y], (5) ffmpegcv GPU-accelerated video I/O, (6) VidGear multi-threaded streaming, (7) Decord batch video loading for ML, (8) PyAV frame-level processing, (9) Audio stream preservation with video filters, (10) Memory-efficient frame generators, (11) OpenCV + FFmpeg + Modal parallel processing, (12) Pipe frames between FFmpeg and OpenCV. Provides: Color format conversion patterns, coordinate system gotchas, library selection guide, memory management, subprocess pipe patterns, GPU-accelerated alternatives to cv2.VideoCapture. Ensures: Correct integration between FFmpeg and OpenCV without color/coordinate bugs. See also: ffmpeg-python-integration-reference for type-safe parameter mappings.
Create, manage, and execute agent tools (claude, codex) inside Docker sandboxes for isolated code execution. Use when running agent loops, spawning tool subprocesses, or any task requiring process isolation. Triggers on "sandbox", "isolated execution", "docker sandbox", "safe agent execution", or when working on agent loop infrastructure.