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Execute qualquer Skill no Manus com um clique

thumbgate-feedback

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Atualizado26 de maio de 2026 às 00:15

Capture thumbs up/down feedback into structured memories and prevention rules. Use when user gives explicit quality signals about agent work (e.g. "that worked", "that failed", "thumbs up/down"). Do NOT use for general questions, code generation, file operations, or any task that is not explicit feedback on prior agent output.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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Fonte

IgorGanapolsky

IgorGanapolsky/ThumbGate

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Especialistas em gestão de projetosNegócios e Operações Financeiras·SOC 13-1082

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SKILL.md

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name	thumbgate-feedback
description	Capture thumbs up/down feedback into structured memories and prevention rules. Use when user gives explicit quality signals about agent work (e.g. "that worked", "that failed", "thumbs up/down"). Do NOT use for general questions, code generation, file operations, or any task that is not explicit feedback on prior agent output.
triggers	["thumbs up","thumbs down","that worked","that failed"]
negative_triggers	["generate code","search files","explain this","run tests"]

ThumbGate Feedback Skill

When user provides feedback, execute:

# negative
npx thumbgate capture \
  --feedback=down \
  --context="<what failed>" \
  --what-went-wrong="<specific failure>" \
  --what-to-change="<prevention action>" \
  --tags="<domain>,regression"

# positive
npx thumbgate capture \
  --feedback=up \
  --context="<what succeeded>" \
  --what-worked="<repeatable pattern>" \
  --tags="<domain>,fix"

At session start, run:

npx thumbgate stats
npx thumbgate lessons

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ThumbGate provides pre-action gates for AI coding agents. It captures thumbs-up/down feedback on agent actions, auto-promotes repeated failures into prevention rules, and blocks known-bad tool calls via PreToolUse hooks. Trigger when the user wants to add safety guardrails to an AI agent workflow, capture structured feedback on agent output, generate prevention rules from failure patterns, gate high-risk actions before execution, or export DPO training pairs from production feedback. Works with any MCP-compatible agent including Cursor, Codex, Gemini CLI, Amp, and OpenCode.

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Capture thumbs up/down feedback into structured memories and prevention rules. Require one sentence of why before claiming memory promotion. Use when user gives explicit quality signals about agent work (e.g. "that worked", "that failed", "thumbs up/down"). Do NOT use for general questions, code generation, file operations, or any task that is not explicit feedback on prior agent output.

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Give your agent persistent cross-session memory — recall what went wrong on similar tasks before starting, then capture whether the work succeeded or failed so repeated mistakes auto-promote into prevention rules. Runs locally via the ThumbGate MCP server (recall, capture_feedback, prevention_rules, feedback_stats) — no API key needed. Use when the user says "recall", "what went wrong last time", "remember this for next time", "capture feedback", "thumbs up/down on that", or at the start of a new task or session. Do NOT use when the user wants to force one specific mistake into an enforced block gate (use the thumbgate-guard skill), to list rules that already exist (thumbgate-rules), or to check ThumbGate wiring (thumbgate-doctor).

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Course-correct from over-planning to execution — when the agent has produced a plan, research, or options instead of doing work the user already approved, drop the analysis and execute the smallest end-to-end action now (branch, run, deploy, verify). Use when the user says "stop planning, just do it", "why are you researching, execute", "just ship it", "enough analysis", or pushes back that you keep proposing instead of acting on an already-decided task. Do NOT use when the task is genuinely undecided and needs a plan first, when the user explicitly asked for research/options/a design, or for routine work where no over-planning has occurred — acting on an unscoped or destructive task is its own failure.

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Show ThumbGate's enforcement record — how many risky actions were actually blocked versus warned, which gates fire most, the tokens/damage saved, and the full feedback to check to rejection pipeline. Reads live enforcement counters via the gate_stats and enforcement_matrix MCP tools (CLI fallback `npx thumbgate gate-stats`). Use when the user says "what has ThumbGate blocked", "show gate stats", "is enforcement working", "how many tokens did we save", "show the enforcement matrix", or "what got stopped". Do NOT use to list rule DEFINITIONS that exist (use the thumbgate-rules skill), to create a new rule (use the thumbgate-guard skill), or to check whether ThumbGate is installed and wired (use the thumbgate-doctor skill).

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name	thumbgate-feedback
description	Capture thumbs up/down feedback into structured memories and prevention rules. Use when user gives explicit quality signals about agent work (e.g. "that worked", "that failed", "thumbs up/down"). Do NOT use for general questions, code generation, file operations, or any task that is not explicit feedback on prior agent output.
triggers	["thumbs up","thumbs down","that worked","that failed"]
negative_triggers	["generate code","search files","explain this","run tests"]

ThumbGate Feedback Skill

When user provides feedback, execute:

# negative
npx thumbgate capture \
  --feedback=down \
  --context="<what failed>" \
  --what-went-wrong="<specific failure>" \
  --what-to-change="<prevention action>" \
  --tags="<domain>,regression"

# positive
npx thumbgate capture \
  --feedback=up \
  --context="<what succeeded>" \
  --what-worked="<repeatable pattern>" \
  --tags="<domain>,fix"

At session start, run:

npx thumbgate stats
npx thumbgate lessons