- name
- thumbgate
- description
- Stop your AI from making the same mistake twice. Pre-Action Gates that block repeat hallucinations, retry loops, and known-bad tool calls before they reach the model — zero tokens spent on mistakes you've already corrected. Works with Claude Code, Cursor, Codex, Gemini CLI, Amp, OpenCode, and any MCP-compatible agent.
- homepage
- https://thumbgate-production.up.railway.app
- metadata
- {"clawdbot":{"emoji":"🧰","requires":{"bins":["thumbgate"]},"install":[{"id":"npm","kind":"npm","module":"thumbgate","bins":["thumbgate"],"label":"Install ThumbGate (npm)"}]}}
ThumbGate — Pre-Action Gates for AI Agents
Stop your AI from making the same mistake twice.
Repeated AI mistakes cost real money in tokens. Thumbs-down once — ThumbGate blocks that exact pattern on every future call, across every agent you use.
- npm:
thumbgate - Dashboard: https://thumbgate-production.up.railway.app/dashboard
- Repo: https://github.com/IgorGanapolsky/ThumbGate (MIT)
Quick Start
npx thumbgate initBootstraps .thumbgate/ and wires PreToolUse hooks into your agent. Works out-of-the-box with Claude Code, Cursor, Codex, Gemini CLI, Amp, OpenCode, and any MCP-compatible agent.
Core Commands
thumbgate capture "Never run --force push to main" # create a rule
thumbgate gates list # see active gates
thumbgate feedback down "agent ignored file paths" # capture a thumbs-down
thumbgate lessons search "DROP TABLE" # recall prior lessons
thumbgate dashboard # open the local dashboardWhat ThumbGate Does
- Capture — every thumbs-down on a bad agent action becomes a structured lesson.
- Distill — lessons merge into prevention rules via history-aware synthesis.
- Enforce —
PreToolUsehooks physically block matching tool calls before the model is invoked. Zero tokens spent on the repeat. - Measure — live "tokens saved" counter in the dashboard puts a dollar number on every block.
When to Use This Skill
- The agent keeps hallucinating the same wrong import, wrong file path, or wrong command.
- You want destructive operations (
DROP TABLE,git push --force, etc.) blocked at the tool-call layer, not the prompt layer. - You need an audit trail of *what the agent tried to do and was prevented from doing* for compliance / review.
- You want DPO-ready preference pairs exported from your real feedback for fine-tuning.
Pricing
- Free CLI — 3 captures/day, 1 rule, 1 agent. MIT open source.
- Pro ($19/mo or $149/yr) — unlimited captures + rules, personal local dashboard, DPO export.
- Team ($49/seat/mo) — shared hosted lesson DB, org dashboard, workflow governance.
Dashboard + live tokens-saved counter: https://thumbgate-production.up.railway.app/dashboard