session-deep-dive

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Deep qualitative analysis of high-signal sessions. Spawns subagents with v2 template, synthesizes patterns, compares against known findings. Use after /session-scan.

AI & Automation 437 stars 25 forks Updated today MIT

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# Session Deep Dive (Tier 2) Qualitative analysis of high-signal sessions identified by `/session-scan`. Spawns subagents with pre-computed metrics context for focused analysis. ## Requirements Requires **ccrider MCP**. If not available: > ccrider MCP is required. See: <https://github.com/neilberkman/ccrider> ## Usage ``` /session-deep-dive ffa155ee-ed8a-492c-8797-878fcbec4d9e /session-deep-dive --last # Most recent Tier 2 eligible /session-deep-dive --from-scan # All Tier 2 eligible from last scan /session-deep-dive --from-scan --compare .claude/UPDATED_PLUGIN_REPORT_160_SESSIONS.md ``` ## Pipeline ### Step 1: Resolve Target Sessions From `$ARGUMENTS`: - **Session ID**: Single session to analyze - **`--last`**: Most recent Tier 2 eligible session from metrics.jsonl - **`--from-scan`**: All sessions where `tier2_eligible: true` AND `tier2_completed: false` in `.claude/session-metrics/metrics.jsonl` - **`--compare REPORT.md`**: Previous report to compare against (default: most recent `.claude/session-analysis/insights-*.md`) If no metrics.jsonl exists, tell the user: > No metrics found. Run `/session-scan` first to discover and score sessions. ### Step 2: Load Pre-computed Metrics For each target session, read its entry from `metrics.jsonl`. Format the metrics as a context block for subagent prompts: ``` ## Pre-computed Metrics (from /session-scan) - Friction: 0.42 (retry_loops: 1, user_corrections: 3, approach_changes: 2) -...

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Author
oliver-kriska
Repository
oliver-kriska/claude-elixir-phoenix
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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