SECURITY REVIEW
Not yet assessed
Review the original instructions and requested permissions before installing.
No security review is available for this catalog entry yet.
Anthropic · Data Analysis / AGENT SKILL
session-report
0
Generate explorable HTML reports of Claude Code token usage, caching, subagents, skills, and costly prompts.
Generate an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.
Understand the trade-offs.
SKILL QUALITY
Not yet assessed
How clearly the skill guides your agent, how complete its workflow is, and how you can check the outcome.
No quality assessment is available for this catalog entry yet.
The full skill.
Original instructions from the publisher’s SKILL.md
# 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:
```sh
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:
```sh
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:
```html
<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).