Turn customer complaints into clear, empathetic, policy-aware reply drafts. ReplyGuard AI suggests issue categories and priorities, flags missing details, handles support CSVs, and prepares replies for human approval.
An AI that predicts the market is everywhere. This is the opposite: a guard that remembers YOUR past trading mistakes and warns you before you repeat one. Keep a small Markdown pattern journal (FOMO chases, thesis-less averaging down, "bubble" misses); before any trade decision the agent scans it and shows your own words back — how it ended last time, and the rules you set for yourself. Runs 100% locally, no API keys, Korean & English. Self-review tool only — not investment advice.
Keeps your AI agent from forgetting who it is. Detects and neutralizes persona drift, rule erosion, and prompt injection attempts — across long conversations. Context isolation, anti-drift enforcement, and graceful override responses built in. Your custom persona stays locked.
This Skill is built on practical expertise in long-running AI workflow control, constraint tracking, handoff reliability, completion evidence, and instruction-change recovery. It helps agents keep the user's first, middle, and latest requirements aligned across multi-step work so older assumptions do not override newer directions and completion is backed by observable evidence.
This Skill is built on practical expertise in AI agent safety, prompt-injection defense, source-to-sink privacy review, tool and MCP metadata integrity, memory provenance checks, autonomous action scoping, and evidence-based verification. It helps agents separate instructions from evidence before tool calls, uploads, publishing, deletion, code execution, or network output.
Forces AI agents to verify every company claim with a Tier 1 source and a date before including it in any job search shortlist — so your research produces fewer, stronger candidates instead of confident guesses.
This Skill is built around practical communication design, family-message tone control, AI guardrail writing, uncertainty labeling, and safe redirection for sensitive topics. It focuses on short parent-friendly wording, blame reduction, boundary-setting, fact-check reminders, and avoiding manipulative or overconfident replies.
Prevents AI agents from declaring tasks complete until every requirement is verified with a one-line evidence anchor — when a gate fails, the agent stops and reports rather than proceeding, and only a human can unlock the gate to continue.
Audit AI agents, Skills, MCP configurations, tool permissions, and coding-agent setups for prompt injection, excessive agency, credential exposure, data leakage, unsafe code execution, supply-chain risks, memory risks, missing approval controls, and runaway autonomy. Get a calibrated Security Score, Audit Confidence, evidence-backed findings, remediation steps, verification checks, and residual-risk analysis.