mcpField
S
session-report

session-report

github.com/anthropicsAgent workflows45.1k3.8k installsUpdated 1d ago
Repository

About session-report

A Claude Code skill that turns usage data from Claude Code sessions into a self-contained HTML report. It includes usage breakdowns and concise findings and suggestions based on the analyzer output.

Key features

  1. 01Analyze session usage over a chosen period
  2. 02Render metrics from JSON in an HTML template
  3. 03Summarize findings with figures and context
  4. 04Add suggestions tied to report data

Use cases

  1. 01Review recent Claude Code token usage
  2. 02Compare usage across projects and skills
  3. 03Spot cache breaks or unusually large prompts
  4. 04Save a shareable HTML usage report

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/anthropics/claude-plugins-official --skill session-report

After installing, type/session-reportin Claude Code to confirm it loaded.

Bundled filesanalyze-sessions.mjstemplate.html

Details

From the project README

Session Report

Produce a self-contained HTML report of Claude Code usage and save it to the current working directory.

Steps

  1. Get data. Run the bundled analyzer (default window: last 7 days; honor a different range if the user passed one, e.g. 24h, 30d, or all). The script analyze-sessions.mjs lives in the same directory as this SKILL.md — use its absolute path:

    node <skill-dir>/analyze-sessions.mjs --json --since 7d > /tmp/session-report.json

    For all-time, omit --since.

  2. Read /tmp/session-report.json. Skim overall, by_project, by_subagent_type, by_skill, cache_breaks, top_prompts.

  3. Copy the template (also bundled alongside this SKILL.md) to the output path in the current working directory:

    cp <skill-dir>/template.html ./session-report-$(date +%Y%m%d-%H%M).html

  4. Edit the output file (use Edit, not Write — preserve the template's JS/CSS):

    • Replace the contents of <script id="report-data" type="application/json"> with the full JSON from step 1. The page's JS renders the hero total, all tables, bars, and drill-downs from this blob automatically.
    • Fill the <!-- AGENT: anomalies --> block with 3–5 one-line findings. Express figures as a % of total tokens wherever possible (total = overall.input_tokens.total + overall.output_tokens). One line per finding, exact markup: 
      <div class="take bad"><div class="fig">41.2%</div><div class="txt"><b>cc-monitor</b> consumed 41% of the week across just 3 sessions</div></div>
      Classes: .take bad for waste/anomalies (red), .take good for healthy signals (green), .take info for neutral facts (blue). The .fig is one short number (a %, a count, or a multiplier like 12×). The .txt is one plain-English sentence naming the project/skill/prompt; wrap the subject in <b>. Look for: a project or skill eating a disproportionate share, cache-hit <85%, a single prompt >2% of total, subagent types averaging >1M tokens/call, cache breaks clustering.
    • Fill the <!-- AGENT: optimizations --> block (at the bottom of the page) with 1–4 <div class="callout"> suggestions tied to specific rows (e.g. "/weekly-status spawned 7 subagents for 8.1% of total — scope it to fewer parallel agents").
    • Do not restructure existing sections.

  5. Report the saved file path to the user. Do not open it or render it.

Notes

  • The template is the source of interactivity (sorting, expand/collapse, block-char bars). Your job is data + narrative, not markup.
  • Keep commentary terse and specific — reference actual project names, numbers, timestamps from the JSON.
  • top_prompts already includes subagent tokens and rolls task-notification continuations into the originating prompt.
  • If the JSON is >2MB, trim top_prompts to 100 entries and cache_breaks to 100 before embedding (they should already be capped).

Comments

Markdown supported