Opaline

Opaline is a team-wide analytics platform for Claude Code and Codex sessions. It provides message-level insights, tracking token cost, time, and skill usage for every single message across your team's sessions. Designed for development teams using AI coding assistants, Opaline aims to pull back the curtain on coding sessions and turn teammate struggle into learning. By capturing granular data, it helps teams understand exactly how their AI tools are being used, where costs are accumulating, and where teammates might need support. As AI coding assistants like Claude Code and Codex become integral to development workflows, teams often lack visibility into their usage and impact. Without proper analytics, it's challenging to optimize costs, identify struggling team members, or measure the effectiveness of these tools. Opaline addresses this gap by providing a comprehensive dashboard that aggregates data from every session. It answers critical questions: How much are we spending on API calls? Who is using the tools most? Which repositories or models drive the highest costs? What language patterns emerge during sessions? This visibility is essential for making informed decisions about AI adoption and team training. One of Opaline's core features is detailed cost tracking. The dashboard displays total API cost for a selected period, such as $3,200.99 for August 1-31, 2026. It includes a daily UTC chart, allowing teams to see spending trends over time. Cost is broken down by individual member, repository, and model, providing a multi-dimensional view of expenses. For example, in the demo, Rafa spent $1,175.59 (37% of total), Evren $1,046.61 (33%), and Marc $978.79 (31%). This per-member breakdown helps identify high usage and enables accountability. It also helps in budgeting and forecasting future AI costs. The repository and model breakdowns add another layer of insight. Opaline shows API cost per repository, such as evrendom/rudel at $3,104.04 (97%) and opalinehq/athena at $96.95 (3%). Similarly, it breaks down cost by model, like GPT 5.6 Sol at $2,051.43 (64%) and Fable 5 at $1,149.56 (36%). These breakdowns help teams understand which projects and models consume the most resources. They can then make strategic decisions, such as optimizing prompts, switching models, or allocating budgets more effectively. This level of detail is invaluable for teams managing multiple projects and AI models. Opaline also tracks session and usage metrics. It records the number of sessions (e.g., 85), agent runs (e.g., 1,864), and language signals (e.g., 385). Language signals are particularly unique: they capture specific phrases used during sessions, such as "You're absolutely right" from Claude or "I know, you f*cking idiot" from a frustrated teammate. These signals can reveal patterns of interaction and emotional tone. By surfacing these phrases, Opaline helps teams turn moments of struggle into learning opportunities. For instance, if a teammate frequently expresses frustration, managers can offer assistance or adjust workflows. This feature aligns with the product's goal of turning teammate struggle into learning. The platform is built as an open-source CLI tool, installed via `npx opaline@latest`. It integrates with Claude Code and Codex sessions, collecting message-level data without disrupting existing workflows. The data is then aggregated and presented in a web-based dashboard. The dashboard uses daily UTC grouping for consistent time-based analysis. It includes visualizations such as cost charts and tables for members, repositories, and models. The product demo showcases a sample period from August 1 to August 31, 2026, illustrating how the analytics appear in practice. Being MIT open source, Opaline allows teams to self-host, customize, and contribute to the project. The benefits of using Opaline are clear for teams adopting AI coding assistants. First, it provides cost transparency, helping teams avoid unexpected API bills. Second, it fosters a culture of learning by identifying struggles and enabling targeted support. Third, it offers data-driven insights for optimizing tool usage and model selection. Fourth, it promotes accountability through per-member metrics. Fifth, it saves time by automating the collection and visualization of session data. Ultimately, Opaline empowers teams to get the most out of their AI investments while supporting their developers. Concrete use cases illustrate Opaline's value. A team lead can use the dashboard to monitor monthly API spend and identify the most expensive repository. An engineering manager can spot a teammate with high frustration signals and schedule a mentoring session. A developer can review daily cost trends to adjust their own usage habits. A team can compare model costs to decide which model to standardize on. An organization can use Opaline during onboarding to show new hires how to interact effectively with AI agents. These scenarios demonstrate how Opaline turns raw session data into actionable insights. Opaline is designed for development teams that use Claude Code and Codex. This includes engineering managers, team leads, and individual contributors who want visibility into their AI usage. It is also suitable for open-source maintainers and organizations that prioritize open-source tools. Since it is MIT licensed and free to use, it appeals to teams of all sizes, from startups to enterprises. The product requires no complex setup, just a simple `npx` command. It integrates seamlessly with existing Claude Code and Codex workflows, making adoption straightforward. In summary, Opaline brings PostHog-style analytics to AI coding sessions. It offers team-wide, message-level tracking of token cost, time, and skill usage. By making usage visible, it helps teams control costs, support struggling teammates, and learn from every session. Whether you are a small team or a large organization, Opaline provides the insights needed to optimize your AI coding assistant usage. Its open-source nature and free pricing make it accessible to all. With Opaline, you can pull back the curtain on your coding sessions and turn every interaction into an opportunity for growth.