failproofai

作者 FailproofAI已验证

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

1,387
Stars
287
Forks
MDX
语言
2026/8/23
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⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/FailproofAI/failproofai

快速入门

使用 failproofai 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

failproof ai

FailproofAI%2Ffailproofai | Trendshift

npm CI Supply Chain Discord Reddit Docs License

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.

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

PolicyWhat it blocks
sanitize-api-keysAPI keys leaking into the agent's context
block-env-filesReads of .env and other secret files
warn-repeated-tool-callsThe agent looping on the same call
block-sudoPrivilege escalation
warn-destructive-sqlDROP, TRUNCATE, unbounded DELETE
block-terraform / block-kubectlUnreviewed changes to live infrastructure
block-rm-rfRecursive file deletion
block-force-push / block-push-mastergit 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:

DecisionEffect
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
QuickstartInstall, connect a harness, see the first run
ConceptsHow the hook system works
Supported harnessesAll 12, and what each one can enforce
Observe
SessionsFollow a run: models, tools, errors, latency
Read a traceWhat the execution graph is telling you
AuditsFind failure patterns across many sessions
Local dashboardlocalhost:8020, no account needed
Enforce
Built-in policiesAll 40 policies with parameters
Custom policiesWrite your own
ConfigurationConfig scopes and merge rules
Instrument your own agent
Python SDKReport runs from an agent with no harness
Policy SDKallow / 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.

常见问题

What is failproofai?

failproofai is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by FailproofAI. 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. It has 1,387 GitHub stars.

Is failproofai safe to use?

Yes. failproofai passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install failproofai?

Clone the repository with "git clone https://github.com/FailproofAI/failproofai" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is failproofai written in?

failproofai is primarily written in MDX. It is open-source under FailproofAI on GitHub, so you can review or fork the full source.

Are there alternatives to failproofai?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh failproofai against similar tools.

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failproofai — Claude Code AI Skill | SkillTip