Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/oliver-kriska/claude-elixir-phoenixnpx agentmods add skills/oliver-kriska/claude-elixir-phoenix/session-trendsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oliver-kriska/claude-elixir-phoenix/session-trends)<a href="https://agentmods.dev/skills/oliver-kriska/claude-elixir-phoenix/session-trends"><img src="https://agentmods.dev/badge/skills/oliver-kriska/claude-elixir-phoenix/session-trends/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oliver-kriska/claude-elixir-phoenix/session-trends"><img src="https://agentmods.dev/badge/skills/oliver-kriska/claude-elixir-phoenix/session-trends.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.01220 |
| Opus 5 | $0.00015 | $0.00610 |
| Sonnet 5 | $0.00006 | $0.00244 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
session-trends scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
/session-trends --html out.html # Write HTML report with ASCII bars
For pure context-window stats (max prompt tokens, ctx %, compaction rate)
across raw Claude Code JSONL files, see the --scan-jsonl mode of
compute-metrics.py (inspired by badlogic / earendil-works/pi).
Pipeline
Step 1: Parse Arguments
Extract from $ARGUMENTS:
--window WINDOW: Time window —7d,30d, orall(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-scanfirst.
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
| Metric | 7 days | 30 days | All time |
|-------------------------|--------|---------|----------|
| Sessions | 12 | 45 | 165 |
| Avg friction | 0.28 | 0.24 | 0.22 |
| Max friction | 0.72 | 0.72 | 0.89 |
| Avg opportunity | 0.35 | 0.30 | 0.28 |
| Tier 2 eligible | 40% | 33% | 30% |
| Plugin adoption | 12% | 10% | 8% |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 146 lines · 31 tokens per session scan A fae5217dba4b
session-trends is a skill published in the GitHub repository oliver-kriska/claude-elixir-phoenix (541 stars, last pushed 4d ago), licensed MIT. It adds 31 tokens to every session and 1,220 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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