claw-reliabilityAgent observability — monitors tool invocations, LLM calls, token usage, costs, and anomalies with pluggable alerts and a real-time dashboard.
Install via ClawdBot CLI:
clawdbot install fiddyrod/claw-reliabilityGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
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http://localhost:8777Audited May 4, 2026 · audit v1.0
Generated Aug 6, 2026
An IT operations team uses the skill to monitor the reliability of their AI-powered support chatbots and backend automation agents. They set up alerts for tool failures and cost spikes, enabling rapid response to anomalies before they impact customers.
A customer service organization deploys AI agents to handle queries. The skill's cost reports help them track token usage and identify inefficient agents, allowing them to optimize their AI spend and reduce operational costs.
A sales team uses AI agents for lead qualification and outreach. The tool reports and anomaly detection reveal which agents have high failure rates, guiding refinement of their prompts and workflows to improve conversion rates.
A software development company uses the skill to monitor its AI coding assistants. By tracking tool invocations and failure rates, developers can quickly identify and fix issues in their AI-assisted development pipeline, enhancing productivity.
The product offers core monitoring for free but charges for advanced features like anomaly detection, custom alerts, and dashboard access. Revenue comes from monthly or annual subscriptions from teams needing deeper insights.
Positioned as an enterprise-grade observability solution for AI agents. Revenue is generated through licensing contracts with enterprises, often including custom integrations, SSO, and dedicated support. Pricing is based on agent volume and feature usage.
Charges per metric collected or per agent monitored. This model is suitable for small to medium businesses that prefer a pay-as-you-go structure. Revenue is based on the number of events processed and stored.
💬 Integration Tip
Integrate with your CI/CD pipeline by invoking monitor.py as part of post-deployment testing to automatically verify agent reliability before production rollout.
Scored Aug 6, 2026
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