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- openclaw-agent-wallet
Works with the AI tools you already use
Openclaw Agent Wallet
Add budget limits, approval workflows, and a policy-gated wallet layer to your autonomous agents.
Free
openclaw-agent-wallet
Example session with this skill installed
Setup a wallet policy for my agent with a $50 daily limit and require my approval for any transaction over $10.
- Read your context and instructions
- Compiled the openclaw-agent-wallet
Wallet policy initialized
- Daily Cap: $50.00
- Approval Threshold: >$10.00
- Audit Log: active (vault/audit.jsonl)
The agent now routes all spend requests through the policy engine. Transactions >$10 will remain 'pending' until approved via the CLI.
Connects securely to your tools. The creator never sees your data.
About this skill
Control Agent Spending without Giving Up Keys
The OpenClaw Agent Wallet provides a robust policy and budgeting layer for autonomous agents. It solves the "blank check" problem by sitting between your agent's decision-making logic and your actual funds, ensuring no agent can accidentally or maliciously drain a wallet.
What it does
This skill implements a rigorous spend-gate. Instead of giving an agent direct access to private keys, it forces every transaction through a WalletPolicy engine. It supports hard caps (per transaction, per day, or lifetime), domain-based allow/deny lists, and a human-in-the-loop approval queue for high-value transfers.
- Policy-Based Budgeting: Define strict financial guardrails in JSON.
- Air-Gapped Signing: Communicates with an external signer service via
WALLET_SIGNER_URL, keeping private keys entirely outside the agent's environment. - Human-in-the-Loop: Automatically queues transactions exceeding specific thresholds for manual CLI or webhook approval.
- Immutable Audit Logs: Every success, failure, and manual intervention is recorded in an append-only JSON log for full accountability.
Why use this skill?
Prompting an AI to "be careful with money" is not a security strategy. This skill provides a technical enforcement layer that works regardless of the model's behavior. It is framework-agnostic, working seamlessly with OpenClaw or local Python-based agents, and focuses on the custody boundary—ensuring your credentials stay safe while your agent stays productive.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
Free skills download straight away. Paid skills unlock right after purchase.
- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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