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session-report

Generate an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

cline/skills
설치 방법 보기

포함된 파일(3)

  • SKILL.md3.1 KB
  • analyze-sessions.mjs27.6 KB
  • template.html25.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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).

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