Use to orchestrate a swarm of sub-agents under a CEO pattern when one agent isn't enough but a full visible grid is overkill: break a mission into roles, dispatch them, and coordinate via signal files.
Use to track and cap what an agent run costs: meter token/compute spend, set budgets, and surface cost as a first-class signal so an autonomous agent doesn't quietly burn through its limit.
Use to apply deterministic, zero-LLM code transforms: fast, repeatable edits that don't need a model, so an agent offloads mechanical changes to a cheap tool instead of spending tokens reasoning through them.
Use to author, test, and share agent skills from the command line: scaffold a SKILL.md, validate its structure, and package it for reuse, turning a one-off procedure into a portable capability.
Fiddler AI Observability platform monitors LLM applications for hallucinations, toxicity, bias, and drift, with explainability and alerting for production AI.
Open-source, OpenTelemetry-compliant LLM observability tool by Scale3Labs. It traces calls to all major LLM providers and frameworks with a self-hostable UI.
Literal AI is an observability and evaluation platform for conversational AI. It captures multi-step threads, scores responses, and integrates with Chainlit.
Open-source LLM observability and prompt management platform. It tracks conversations, errors, costs, and user feedback for production AI applications.
Maxim AI is an evaluation and observability platform for AI agents. It supports multi-step trace analysis, prompt testing, and production quality monitoring.
New Relic AI Monitoring instruments LLM calls end-to-end. It traces model invocations, measures token costs, and surfaces anomalies via the New Relic platform.