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failproof ai

FailproofAI%2Ffailproofai | Trendshift

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Translations: 简体中文 · 日本語 · 한국어 · Español · Português · Deutsch · Français · Русский · हिन्दी · Türkçe · Tiếng Việt · Italiano · العربية · עברית

Observability and enforcement for every harness your agents run in. Wherever your agents run, we see it — and we can say no. Failproof hooks 12 agent harnesses — coding CLIs like Claude Code and Codex, chat gateways like Hermes, self-hosted assistants like OpenClaw — capturing every run and blocking dangerous tool calls before they execute. 40 built-in policies. Zero latency. Runs locally.

Failproof AI in action


Supported harnesses

Twelve harnesses in two classes — ten coding CLIs, and two chat and assistant gateways (Hermes, OpenClaw). Same events, same policies, same session history, whichever one your agent runs in.

Agents that run in none of them report through the Python SDK, which gives you tracing, sessions and audits. Enforcement there needs a hook in your own runtime — talk to us and we'll map it.

Claude Code OpenAI Codex GitHub Copilot Cursor Agent OpenCode Pi
Hermes OpenClaw Factory Droid Devin CLI Antigravity CLI Goose

Install

npm install -g failproofai
failproofai policies --install   # or just run `failproofai` and accept the first-run prompt
failproofai

40 built-in policies activate immediately. Dashboard at localhost:8020. Disable the first-run prompt with FAILPROOFAI_NO_FIRST_RUN=1.


What it stops

Policy What it blocks
sanitize-api-keys API keys leaking into the agent's context
block-env-files Reads of .env and other secret files
warn-repeated-tool-calls The agent looping on the same call
block-sudo Privilege escalation
warn-destructive-sql DROP, TRUNCATE, unbounded DELETE
block-terraform / block-kubectl Unreviewed changes to live infrastructure
block-rm-rf Recursive file deletion
block-force-push / block-push-master git push --force, direct pushes to main

The first five apply to any agent that can call a tool. The last three are the developer favourites — coding CLIs are the harness class we cover deepest.

All 40 built-in policies


Your own policies

Drop a file into .failproofai/policies/ — it loads automatically, no flags needed. Commit it and the whole team gets it on next pull.

import { customPolicies, deny, allow } from "failproofai";

customPolicies.add({
  name: "no-production-writes",
  match: { events: ["PreToolUse"] },
  fn: async (ctx) => {
    if (ctx.toolInput?.file_path?.includes("production"))
      return deny("Writes to production paths are blocked.");
    return allow();
  },
});

Three decisions available to every policy:

Decision Effect
allow() Permit the operation
deny(message) Block it — message goes back to the agent
instruct(message) Let it through, but add context to the agent's next prompt

Custom policies guide


Observability

Enforcement is one half. The other half is seeing what the agent actually did.

Run failproofai with no arguments and it serves a dashboard on localhost:8020 reading the run history already on your machine — no account, no signup, nothing leaving the box. You get the session list, the sequence of model calls, tool calls and hook decisions inside each run, what was blocked and what the policy told the agent, and an offline audit (failproofai audit) that scans your history for risky patterns and suggests policies to stop them.

Local dashboard · Read a trace · Local audit

Failproof AI Observability is the hosted side of the same data model, for teams running agents across a fleet: every run from every harness in one place, an execution graph with parallel sub-agents on their own lanes, p50/p95/p99 latency for models, tools and hooks, per-model cost and context-window tracking, error tracking, SQL over your own traces with shareable dashboards, evaluations scored by your own service, scheduled audits that turn recurring failures into evidence-backed findings, and alerts routed to Slack, email or a signed webhook. Self-hosting in your own cluster is available on the Enterprise plan.

Sessions · Audits · Book a demo


Documentation

Start
Quickstart Install, connect a harness, see the first run
Concepts How the hook system works
Supported harnesses All 12, and what each one can enforce
Observe
Sessions Follow a run: models, tools, errors, latency
Read a trace What the execution graph is telling you
Audits Find failure patterns across many sessions
Local dashboard localhost:8020, no account needed
Enforce
Built-in policies All 40 policies with parameters
Custom policies Write your own
Configuration Config scopes and merge rules
Instrument your own agent
Python SDK Report runs from an agent with no harness
Policy SDK allow / deny / instruct reference

License

MIT with Commons Clause — free for internal and personal use; commercial resale of failproofai itself requires a separate agreement. See LICENSE for the full text.


Contributing

See CONTRIBUTING.md. New policies, edge cases, and translations all welcome.

Build before you start. Run bun install && bun run build first. This repo runs failproofai's own hooks on itself, and they resolve the failproofai import against the compiled dist/ bundle — without a build you'll hit Cannot find package 'failproofai' hook errors. Rebuild after changing src/. See Build before the in-repo dev hooks will work.


Built with ❤️ by befailproof.ai in SF and Bengaluru.

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Observability and enforcement for AI agent harnesses. Capture every run and runtime reliability with policy enforcement. 40 built-in policies, a local dashboard, no account required with a generous free cloud plan

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