Tag: feedback-loop
ThumbGate: Safety guardrails for AI agents
ThumbGate provides pre-action gates for AI coding agents by intercepting tool calls to prevent known mistakes. It captures structured feedback and automatically generates prevention rules from repeated failure patterns.
Persistent Agent Memory and Failure Prevention
This tool provides persistent, structured memory for agents across sessions. It allows developers to capture detailed success or failure feedback, automatically generating prevention rules that guide the agent to avoid repeating past mistak…
ThumbGate Feedback Capture Skill
Captures explicit user feedback into structured memories and prevention rules to facilitate agentic learning. It logs context, failures, and corrective actions to refine future agent performance.
ThumbGate Dual-Write Feedback Skill
Captures user feedback simultaneously in Amp MCP memory for in-session recall and thumbgate for DPO export, analytics, and cross-platform prevention rules.
agent feedback capture and action prevention tool
This tool captures agent performance feedback (thumbs-up/down) and uses adaptive mechanisms to generate hard prevention rules. These rules are enforced via PreToolUse hooks, preventing the agent from executing known-bad actions before they …
Feedback-Driven Agent Guardrails for AI Agents
ThumbGate functions as an agent immune system, capturing thumbs-up/down feedback on agent actions. It uses this data to generate hard prevention rules that block known-bad patterns before they can execute, enforcing safety via pre-tool-use …
Evaluates and improves other agent skills
This skill assesses the quality of another agent's output against task requirements, providing structured JSON feedback. It identifies deficiencies, assigns a score (0.0 to 1.0), and specifies any missing instructions for improvement.
Improve Agent Behavior from User Feedback
This skill formalizes the process of converting observed behavioral omissions or failures into durable, permanent process improvements. It captures the miss, selects the smallest appropriate artifact (rule, skill, or workflow), and immediat…
Agent Safety Gates and Failure Pattern Prevention
ThumbGate implements pre-action gates for AI agents, capturing structured thumbs-up/down feedback on tool usage. It automatically generates prevention rules from repeated failures, blocking known-bad patterns before execution via the MCP Pr…
Persistent Agent Memory via MCP
Provides agents with persistent memory across sessions by allowing them to recall past feedback and follow auto-generated prevention rules. The system uses an MCP server to capture task outcomes and track performance trends locally.
Agent Safety Gates for AI Coding Agents
ThumbGate implements pre-action gates for AI agents, capturing structured feedback (thumbs up/down) to identify failure patterns. It automatically generates prevention rules and blocks known-bad tool calls via the MCP PreToolUse hook, signi…
Agent Feedback and Hard Prevention Gateway
ThumbGate acts as an agentic immune system, capturing thumbs-up/down feedback on actions to automatically generate and enforce prevention rules. These rules are implemented as hard PreToolUse hooks, blocking known-bad patterns before the ag…