session-trends

Analyze trends from the metrics ledger. Computes windowed aggregates, fingerprint distributions, and compares against MEMORY.md baselines.

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Install skill "session-trends" with this command: npx skills add oliver-kriska/claude-elixir-phoenix/oliver-kriska-claude-elixir-phoenix-session-trends

Session Trends

Analyze trends from the metrics ledger. Computes windowed aggregates, fingerprint distributions, and compares against MEMORY.md baselines.

Requirements

Requires .claude/session-metrics/metrics.jsonl from /session-scan .

Usage

/session-trends # All windows (7d, 30d, all) /session-trends --window 30d # Specific window only /session-trends --project enaia # Filter by project /session-trends --compare MEMORY.md # Compare against memory baseline

Pipeline

Step 1: Parse Arguments

Extract from $ARGUMENTS :

  • --window WINDOW : Time window — 7d , 30d , or all (default: show all three)

  • --project NAME : Filter metrics by project name

  • --compare PATH : Path to MEMORY.md for baseline comparison (default: auto-detect from .claude/ project memory)

Step 2: Read Metrics Ledger

Read .claude/session-metrics/metrics.jsonl .

If empty or missing:

No metrics found. Run /session-scan first.

If --project specified, filter entries by project field.

Step 3: Compute Trends via Python

python3 .claude/skills/session-scan/references/compute-metrics.py
--trends .claude/session-metrics/metrics.jsonl
--memory {MEMORY_PATH}

Capture the JSON output.

Step 4: Display Trend Report

Format the JSON output as a readable report:

Overview

Total sessions: {N} ({backfilled} backfilled from v1) Date range: {earliest} to {latest}

Window Comparison

Metric7 days30 daysAll time
Sessions1245165
Avg friction0.280.240.22
Max friction0.720.720.89
Avg opportunity0.350.300.28
Tier 2 eligible40%33%30%
Plugin adoption12%10%8%

Fingerprint Distribution

Type7d30dAll
bug-fix41552
feature31248
exploration2830
maintenance1518
review1310
refactoring127

MEMORY.md Comparison (if --compare)

Compare measured values against MEMORY.md claims:

MEMORY.md ClaimMeasuredMatch?
Plugin adoption: 8-12%10.2%Yes
Minimal friction in 40+ of 7468% smoothYes

Step 5: Write trends.json

Write computed trends to .claude/session-metrics/trends.json .

Step 6: Suggest Actions

Based on trends:

  • If friction is increasing: "Friction trending up — run /session-deep-dive --from-scan to investigate"

  • If plugin adoption is growing: "Plugin adoption growing — check which commands drive value"

  • If many Tier 2 eligible: "{N} sessions need deep analysis"

Output Files

File Purpose

.claude/session-metrics/trends.json

Computed trend data

Common Queries

See references/trend-queries.md for interpreting specific trend patterns.

Iron Laws

  • ALWAYS use Python for computation — no manual aggregation

  • NEVER modify metrics.jsonl — read-only for trends

  • ALWAYS show window comparison — single numbers lack context

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