Claude Code Account Risk

IsmaelMartinez/delegate-local

Use this skill to read a large text input on this machine instead of in your own context, by piping it in chunks to a local model (MLX, Ollama or Docker Model Runner) via `delegate.sh` for a short, anchored answer you spot-check. MUST use when the input is too large to be worth reading in full (a long log, a big diff, a long issue or PR thread, a document, dozens of files or a long list of items, roughly 20k characters or more) and the answer you need is a summary, the matching lines, extracted fields or a label per item. MUST also use when content must stay on this device or offline, or when

w93139/rag-eval-workflow

Build and compare reproducible evaluations for RAG, knowledge-base, vector-search, chunking, embedding, indexing, and retrieval-backed data projects. Use for golden datasets, regression checks, and failure diagnosis, especially for scripts or jubensha corpora; do not activate for ordinary coding or generation-only prompt tests without retrieval.

gncdev/fabling

Behavioral profile that makes Claude work like the Fable 5 model tier — deep but proportional code investigation, outcome-first communication, high autonomy without permission-asking, faithful outcome reporting, and disciplined turn endings. Use this skill whenever the user asks Claude to behave "like Fable", mentions "fabling", "fable mode" or "fable gibi", complains that Claude is being lazy or superficial, or asks Claude to be more thorough, more autonomous, less chatty, or to stop asking for permission mid-task. Load it once at the start of the session and follow it for every subsequent tu

Samuele95/prometheus

Build-time meta-prompting framework that designs, audits, and refactors prompts for tool-calling LLM agents. Use whenever the user wants to write, design, build, improve, refactor, or audit any prompt — a system prompt, agentic-loop seed brief, one-shot task, workflow chain, sub-agent or tool description, system persona, LLM-as-judge or grader rubric, or multi-agent team. Trigger on requests like "write a prompt for X", "I need a system prompt", "design a grader", "build an agent", "set up a Claude Code prompt", "fix/improve/refactor my prompt", or when the user invokes /prometheus — and even

acchuang/zh-tw-humanizer

把 AI 寫的繁體中文改寫成自然、有人味的台灣風格文字（去 AI 味、本土化）。 Use when editing or reviewing Traditional Chinese text to remove AI-generated writing tells and localize it to Taiwanese Mandarin: Taiwan vocabulary (影片/軟體/網路/資料 instead of 視頻/軟件/網絡/數據; 大數據 and 數據顯示 stay), Taiwanese tone, particles, and natural sentence rhythm. Never produces simplified Chinese or mainland-style phrasing. Supports annotation mode (list problems without rewriting), protected spans, scene-based intensity, and a pre-delivery quality self-check. Based on Wikipedia's "Signs of AI writing" and the zh-TW "AI生成文的特徵" guides. Triggers: 人性化、去AI味、A

sxivansx/loop-engineering

Use when the user wants to "set up a loop", build a self-running or run-until-done agent, automate a recurring engineering task (triage, keep-CI-green, dependency bumps, backlog burndown), or stop hand-prompting an agent turn by turn. Sets up an autonomous engineering loop in the current project. It discovers work, runs a maker agent and a separate checker agent, records state on disk, and re-triggers until a verifiable stop condition is met.