Audit intermediate Works with: Any AI

Jira Backlog Health Audit From an Export

Table output Has example

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Find stale, duplicate and unready items in a backlog.

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Audit our backlog using this export: [BACKLOG_EXPORT], with key, summary, type, created date, last updated, priority, labels and size where available. Our rules for how long an item may sit untouched: [STALENESS_RULE].

Calculate open items, the age distribution (under 30 days, 30 to 90, 90 to 180, over 180) with counts and percentages, items with no size, items with no description, and items untouched beyond the rule. Detect probable duplicates by comparing summaries and list them in pairs with your confidence. Identify items that read as tasks rather than user value.

Return a table of findings with counts, a list of candidates to close, merge or rewrite, and a clean-up plan that fits in two hours, deleting nothing without the owner's agreement. Do not close anything based on age alone. Keep the tone neutral and avoid names, and show the arithmetic. Show the counts in a table first and the explanation after. If the export lacks a field you need, such as last updated, say which checks you could not run instead of estimating.

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Invented export of 200 open items. Age: under 30 days 40 (20 percent); 30 to 90 days 50 (25); 90 to 180 days 38 (19); over 180 days 72 (36). Total 200.
No size: 64 (32 percent). No description: 28 (14 percent). Untouched beyond the 120-day rule: 61 (30.5 percent).
Probable duplicates: 9 pairs (for example "Export CSV fails" and "CSV export broken").
Candidates: close 20 after owner agreement, merge 9 pairs, rewrite 15 task-like items as user value.
Plan: two hours; nothing deleted without the owner's reply.

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