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Analyze pi session transcripts to discover patterns that could become AGENTS.md rules, skills, or prompt templates. Mines your usage history for automation opportunities.
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Basierend auf der SOC-Berufsklassifikation
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Build LLM-ready code dumps with optional docs, then count tokens with tokencount (o200k-base) against a context budget (for example 272k for GPT-5).
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Multi-model code review. Runs code-review skill with 3 models in parallel, then synthesizes findings.
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| name | session-analyzer |
| description | Analyze pi session transcripts to discover patterns that could become AGENTS.md rules, skills, or prompt templates. Mines your usage history for automation opportunities. |
Extracts and analyzes your pi session transcripts to find recurring patterns that could be automated.
# Extract transcripts for current directory
{baseDir}/analyze.js
# Extract transcripts for specific directory
{baseDir}/analyze.js /path/to/project
# Match multiple dirs by pattern (worktrees, variants, etc.)
{baseDir}/analyze.js --pattern orders-app
# Extract + analyze with subagents
{baseDir}/analyze.js --analyze
# Pattern + analyze (finds all matching session dirs)
{baseDir}/analyze.js --pattern orders-app --analyze
# Custom output directory
{baseDir}/analyze.js --output ./my-analysis --analyze
~/.pi/agent/sessions/
--pattern to match multiple directories (e.g., worktrees, feature branches)Without --analyze:
session-transcripts/
├── session-transcripts-000.txt
├── session-transcripts-001.txt
└── ...
With --analyze:
session-transcripts/
├── session-transcripts-000.txt
├── session-transcripts-000.summary.txt # Pattern analysis
├── session-transcripts-001.txt
├── session-transcripts-001.summary.txt
└── FINAL-SUMMARY.txt # Aggregated findings
Install dependencies (run once):
cd {baseDir}
npm install
Adapted from badlogic/pi-mono gist