Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
AI Agent Financial Observability — monitor, budget, and analyze spending across any AI agent. Track costs, set budgets, detect anomalies, and export metrics...
AI Agent Financial Observability — monitor, budget, and analyze spending across any AI agent. Track costs, set budgets, detect anomalies, and export metrics...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
AI Agent Financial Observability — monitor, budget, and analyze spending across any AI agent.
SpendTracker — Record and settle transactions across any payment rail BudgetManager — Set spending limits with automatic alerts AnomalyDetector — Flag unusual spending patterns MetricsEngine — Track ROI, win rate, burn rate, and runway Dashboard — Built-in HTTP server for live monitoring Exporters — Forward data to JSONL, webhooks, or Prometheus
from agentfinobs import SpendTracker, BudgetManager, BudgetRule tracker = SpendTracker(agent_id="my-agent") budget = BudgetManager(rules=[ BudgetRule(name="hourly", max_amount=10.0, window_seconds=3600) ]) tracker.add_listener(budget) tx = tracker.record(amount=2.50, rail="x402_usdc", counterparty="api-provider") tracker.settle(tx.tx_id, status="confirmed", revenue=5.0)
pip install agentfinobs
Python 3.10+
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.