Claude-Code-Agent-Monitor session-compare
install
source · Clone the upstream repo
git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/ccam-insights/skills/session-compare" ~/.claude/skills/hoangsonww-claude-code-agent-monitor-session-compare && rm -rf "$T"
manifest:
plugins/ccam-insights/skills/session-compare/SKILL.mdsource content
Session Compare
Compare two Claude Code sessions side-by-side using Agent Monitor data.
Input
The user provides: $ARGUMENTS
This may be:
- Two session IDs: "abc123 def456"
- "best vs worst" — compare highest and lowest productivity sessions
- "latest 2" — compare the two most recent sessions
- A session ID + "vs average" — compare one session against the baseline
Procedure
-
Identify sessions to compare:
- If two IDs given: fetch both from
http://localhost:4820/api/sessions/{id} - If "best vs worst": fetch sessions, score by completion + cost efficiency, pick extremes
- If "latest 2":
(default sort: most recently updated first)GET /api/sessions?limit=2 - If "vs average": fetch session + compute averages from last 50 sessions
- If two IDs given: fetch both from
-
Gather detailed data for each session:
- Session metadata:
GET /api/sessions/{id} - Events:
GET /api/events?session_id={id} - Agents:
GET /api/agents?session_id={id} - Cost:
GET /api/pricing/cost/{id}
- Session metadata:
-
Build comparison:
Overview Comparison
Metric Session A Session B Difference Status completed error — Model sonnet-4 sonnet-4 same Duration 12m 34s 45m 12s +32m 38s Total Cost $0.0234 $0.1456 +522% Events 45 187 +315% Tools Used 8 12 +4 Error Count 0 7 +7 Agents 2 5 +3 Token Comparison
Token Type Session A Session B Difference Input N N ±N% Output N N ±N% Cache Read N N ±N% Cache Write N N ±N% Efficiency N% N% ±N% Tool Usage Comparison
- Tools unique to Session A
- Tools unique to Session B
- Shared tools with usage count comparison
- Error rate per tool in each session
Timeline Comparison
- Side-by-side event timeline
- Where sessions diverged in approach
- Key decision points that led to different outcomes
Agent Activity Comparison
- Agent counts and types
- Subagent strategy differences
- Agent success rates
-
Analysis:
- Why one session was more efficient/successful than the other
- Key decisions that made the difference
- Lessons to apply to future sessions
Output Format
Present as a side-by-side comparison report with:
- Executive comparison summary (which session was "better" and why)
- Structured comparison tables with color-coded differences (green = better, red = worse)
- A "Lessons Learned" section with actionable takeaways
- Overall winner declaration with justification