Ask questions like:

{"jql": "project = \"ProjectName\" AND created >= -90d", "dataProcessing": {"language": "typescript", "operations": [{"type": "extract", "fields": ["key", "comments", "created", "component", "team"]}]}, "llmAnalysis": {"type": "sentiment", "input": "comments", "output": "sentiment", "prompt": "Analyze the sentiment in these JIRA comments. Consider the technical context and team dynamics specific to software development. Technical criticism with constructive feedback should be considered neutral, not negative. Only mark as negative if the tone shows frustration, anger, or personal criticism beyond professional feedback. Consider terms like 'bug', 'issue', 'fix needed' as neutral technical language rather than negative sentiment.", "thresholds": {"positive": 0.6, "negative": -0.6}, "fallback": "No comments to analyze"}, "visualization": {"type": "pie", "data": {"labels": "sentiment", "values": "count", "fallback": "No sentiment data available"}, "title": "Comment Sentiment Distribution (Last 90 Days)", "legend": {"position": "right"}}}
{"jql": "project = \"ProjectName\" AND issuetype = Story AND created >= -90d", "dataProcessing": {"language": "typescript", "operations": [{"type": "extract", "fields": ["key", "component", "storyPoints", "created"]}, {"type": "aggregate", "function": "sum", "field": "storyPoints", "groupBy": "component"}]}, "visualization": {"type": "bar", "data": {"x": "component", "y": "storyPoints", "fallback": "No stories found in last 90 days"}, "title": "Story Points by Component (Last 90 Days)", "xAxis": {"title": "Component"}, "yAxis": {"title": "Story Points"}}}
{"jql": "project = \"ProjectName\" AND blocked = true AND created >= -90d", "dataProcessing": {"language": "typescript", "operations": [{"type": "extract", "fields": ["key", "blockerType", "created"]}, {"type": "aggregate", "function": "count", "groupBy": "blockerType"}]}, "visualization": {"type": "pie", "data": {"labels": "blockerType", "values": "count", "fallback": "No blockers found in last 90 days"}, "title": "Issue Blocker Distribution (Last 90 Days)", "legend": {"position": "right"}, "percentage": true}}
{ "jql": "project = \"ProjectName\" AND created >= -90d", "dataProcessing": { "language": "typescript", "operations": [ {"type": "extract", "fields": ["key", "comments", "created"]}, {"type": "sentiment", "input": "comments", "output": "sentiment", "as": "sentimentAnalysis"}, {"type": "groupBy", "field": "sentiment", "as": "sentimentGroups"}, {"type": "addField", "field": "summaryText", "value": "Sentiment analysis summary of JIRA comments", "as": "textSummary"} ] }, "llmAnalysis": { "type": "sentiment", "input": "comments", "output": "sentiment", "prompt": "Analyze the sentiment in these JIRA issue comments within the context of software development. Focus on the textual content of the comments. Consider the technical nature of the comments and the professional context. Guidelines: 1) Technical language and bug reports are neutral, not negative. 2) Constructive criticism should be considered neutral. 3) Expressions of frustration with systems or processes may be negative, but factual descriptions of problems are neutral. 4) Positive sentiment includes expressions of appreciation, success reports, or enthusiasm. 5) Negative sentiment includes expressions of significant frustration, blame, dismissive language, or interpersonal conflict. Classify the overall sentiment as one of: [positive, neutral, negative]. If there are multiple comments with different sentiments, weigh recent comments more heavily. Provide a confidence score (0-1) with your classification. Output a JSON object with sentiment, confidence, and evidence (brief quotes supporting your classification).", "thresholds": {"positive": 0.6, "negative": -0.6}, "fallback": "No comments to analyze" }, "visualization": { "type": "text", "title": "Comment Sentiment Analysis (Last 90 Days)", "data": "llmAnalysis" } }
{"source":"github","query":{"repo":"organization/repository","timeRange":{"start":"-6m","end":"now"},"activityTypes":["pull_request.merged"]},"dataProcessing":{"language":"typescript","operations":[{"type":"extract","fields":["id","author","created_at","merged_at","linked_issues","changes"]},{"type":"codeMetrics","measure":"linesChanged","filter":"linked_issues.length > 0","maxLines":1,"outputField":"singleLineFixes"},{"type":"sort","field":"singleLineFixes","order":"desc"}]},"badgeTracking":{"badges":["one-liner-wizard"],"timeframe":"halfyear","assignTo":"author"},"visualization":{"type":"badgeBoard","data":{"users":"author","badges":"one-liner-wizard","fallback":"No one-line fixes found that resolved issues"},"title":"One-Liner Wizard Badge Earners","layout":"grid"}}