WakaTime
Engineering managers ask questions about coding hours, project allocation, and team velocity. Your AI agent queries WakaTime in real time and delivers clear answers. No more digging through dashboards or exporting CSVs. Developer metrics, delivered through conversation.
Your AI agent connects to WakaTime's tracking data, turning raw coding statistics into actionable answers about projects, languages, and developer productivity.
WakaTime
See how engineering teams use AI agents with WakaTime to surface coding metrics, track goals, and understand project time allocation without leaving their chat window.
An engineering lead prepares for a sprint retro and asks the AI agent how many hours the team logged on the main project last two weeks. The agent retrieves WakaTime insights for that date range and project, breaking down time by language and developer. The retro starts with real data, not guesses. Sprint planning accuracy improves immediately.
Each morning, a developer asks the AI agent what they worked on yesterday. The agent pulls their WakaTime coding insights for the previous day, listing projects, languages, and total active coding time. The developer gets a quick summary for their standup update. No manual timesheets, no forgotten tasks.
A developer committed to 20 hours of deep coding per week asks how they are tracking this week. Your AI Agent checks their WakaTime goal progress, shows they have 14 hours logged by Thursday, and suggests they are on pace. Developers stay accountable to personal productivity targets without checking dashboards.
WakaTime
FAQs
The agent uses WakaTime's Insights API, specifying insight types like 'projects', 'languages', or 'best_day' along with a time range. It fetches data in real time and presents it conversationally. All standard WakaTime insight types are supported including weekday breakdowns and daily averages.
Tars requests read_summaries, read_summaries.editors, and read_summaries.languages scopes. These provide read-only access to coding activity data. Tars never writes data to your WakaTime account or modifies any settings.
Yes. The agent retrieves language-specific insights from WakaTime, showing hours and percentages for each language used during any time period. Ask 'How much Python did I write last month?' and the agent returns precise breakdowns from your WakaTime data.
No. Tars queries WakaTime's API live during each conversation. Your coding activity, project names, and productivity data are fetched on demand and used only for the current response. No historical coding data is cached or stored by Tars.
The agent can retrieve leaderboard data that ranks developers by coding activity. For individual team comparisons, each member needs to authorize WakaTime OAuth access. The agent then fetches and compares their respective insights within a single conversation.
The WakaTime dashboard requires you to log in, navigate charts, and interpret graphs. Tars lets you ask questions naturally, like 'How many hours on project X this sprint?' and get an immediate text answer. It also works in Slack and WhatsApp where your team already communicates.
The agent relies on data WakaTime has collected. If a plugin stops tracking, the agent's insights will reflect the gap. When asked, it can report the last machine seen and when data was last received, helping identify the issue quickly.
Yes. Both the all-time stats and insights endpoints accept an optional project parameter. The agent can filter results to show coding time, languages, and activity for a single project, which is useful for client billing or sprint reviews.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
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