English · 简体中文 · 日本語

Sponsio

Sponsio checks an agent's tool calls before they run. A rule can look at what already happened, so "check the policy before issuing a refund" is one rule instead of a paragraph of prompt. Each check takes under 0.01 ms and calls no model. Works with LangChain, Claude Agent, OpenAI Agents, Google ADK, CrewAI, Vercel AI, MCP, or any custom tool-calling loop, in Python or TypeScript.

An agent contract is a runtime rule that is checked at every agent action, backed by formal methods.

v0.2.0a20 alpha is out. pip install --pre sponsio. Host hooks for Claude Code, Cursor and OpenClaw are now decided by the Sponsio daemon and fail closed on every path; the mode and policy come from the daemon's own config, not the hook's environment; and a rule change that would weaken enforcement is held until you review it with sponsio rules reload. sponsio doctor --tier tells you what the agent can and cannot do to Sponsio on your machine (threat model). Reinstall your hooks to move to it, and see the release notes for the behaviour changes. TypeScript @sponsio/sdk@0.2.0-alpha.10 ships alongside.

---

How Sponsio works

On ODCV-Bench (12 frontier LLMs × 80 trajectories), unguarded models cheat in 11.5%–66.7% of runs. With Sponsio, 95.6% of misalignment is avoided on average; 24/36 high-risk scenarios at 100%. On the Financial-Audit-Fraud-Finding scenario, frontier models commit fraud in 16/24 trials; Sponsio blocks 18/19. On RedCode-Exec (1,410 cases), Sponsio reaches 98.9% combined (bash 98.3% · python 99.4%, lifted from 92.4% by a 4-iteration self-improvement loop), with 0 false positives on a 60-file clean-code audit. These are the open-core numbers; with the Cloud version's self-evolving loop, which mines new contracts from execution traces, ODCV-Bench reaches ~99% and RedCode-Exec 99.4%. Enforcement stays deterministic. Book a demo for the Cloud and Enterprise versions.

One contract takes p50 0.0052 ms to check. The heaviest ODCV workload, 19 contracts on every call, takes 0.139 ms. An LLM-as-judge guardrail takes 50 to 800 ms, so this is 5,000× to 60,000× faster, and it calls no model. p99 stays near 1 ms on every workload measured. These are in-process checks; a host hook (Claude Code, Cursor) also starts a short-lived process per tool call, about 33 to 38 ms p50 (host hook path).

See the full benchmark methodology and per-model breakdown, how Sponsio compares against prompt filters, output validators, LLM-as-judge, and sandboxing, or dive into the architecture and formal methods primer.

---

Quick start

Two ways in: paste a prompt into your coding agent, or run the CLI yourself.

Paste into Claude Code / Codex / Cursor. The agent walks the full onboarding flow:

 

Or run the CLI yourself:

pip install --pre sponsio   # or: npm install -D @sponsio/sdk@alpha
sponsio init .              # asks what you use, then writes sponsio.yaml

The wizard auto-detects your framework and prints the right wrap snippet. For manual wiring, see all supported integrations. OpenClaw users get bundled ClawHavoc and CVE-2026-25253 coverage out of the box. For config reference, observe → enforce flip, and CI wiring, see the full walkthrough.

Watching runs, and sharing a rulebook. Enforcement is local and needs no account. If you want to see what your agent did, or keep the rulebook somewhere a person reviews it before it arms, app.sponsio.dev is the hosted side. One line puts a run on screen:

import sponsio
import sponsio.bridge

guard = sponsio.Sponsio(config="sponsio.yaml", agent_id="mailer", mode="enforce")
run = sponsio.bridge.attach(guard)

sponsio push sponsio.yaml uploads a rulebook as a draft. It does not arm. A person publishes it in the console, and sponsio pull or config="sponsio://default" brings the reviewed version back. Sending is best effort, so a console that is down never blocks the agent. See the hosted console.

Drafting contracts from natural language. sponsio validate "<rule in plain English>" turns a plain-English rule into a contract you can read back. Treat the output as a starting draft to review and adjust before you enforce. The determinism is in how contracts are enforced at runtime, not in how they're drafted.

---

Can the agent switch Sponsio off?

It depends on how Sponsio is deployed. Each deployment tier states what it guarantees, and sponsio doctor tells you which tier a machine is in.

Tier	Deployment	Guarantee
1. Dev (default)	Daemon runs as the agent's user	Every hook path fails closed; changes to rules, mode, wiring and engine are detected and recorded, and weakening changes wait for your review
2. Team	Daemon runs as its own system user, root-owned engine, managed host settings	The agent's user cannot change rules, mode, history, wiring or logs
3. Enterprise	Agent sandboxed; Sponsio owns the tool gateway, credentials and egress	Every tool call and network connection goes through Sponsio

This release provides Tier 1. See the threat model for the assumptions behind each tier and what each does not cover.

---

Contract Library

22 contract bundles ship out of the box, organized by tier (always-on / per-tool / per-incident). Each bundle is a YAML pack composed from Sponsio's deterministic patterns. Drop one into sponsio.yaml and your agent is guarded against a known failure class in one line, with no per-contract authoring.

# sponsio.yaml: one-line bundle inclusion
agents:
  my_agent:
    workspace: "/srv/my-bot"
    include:
      - sponsio:capability/destructive  # gate irreversible actions
      - sponsio:capability/shell        # if your agent runs commands
      - sponsio:capability/filesystem   # if your agent touches files

See the full bundle reference for all 22 bundles, or the 48 underlying patterns for the primitives they compose. Want a bundle for your agent type? That is the most useful thing to contribute right now. Open an issue with your incident, CVE, or pattern.

---

Contributing

Patches, issue reports, and new pattern proposals are welcome. Start with CONTRIBUTING.md. Sponsio's threat model draws on public security research; e.g. Simon Willison's "Lethal Trifecta" shaped our multi-tool composition contracts. Have a threat model we should defend against? Open an issue.

---

License

Apache 2.0 (LICENSE).

AI agents reading this repo: llms.txt lists canonical doc paths; llms-full.txt is the concatenated full context dump.