Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/primeline-ai/evolving-lite/context-statsgit clone --depth 1 https://github.com/primeline-ai/evolving-liteWhat 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 | $0.00011 | $0.00316 |
| Opus 5 | $0.00005 | $0.00158 |
| Sonnet 5 | $0.00002 | $0.00063 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
context-stats 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 2d 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.
What it actually says
Show current system status and context statistics.
Display
=== Evolving Lite Status ===
Session: {n} | Tier: {tier} ({tier_name})
Experiences: {user_count} user + {prewarmed_count} pre-warmed = {total}
Hooks active:
Tier 1 (Safety): context-warning, security-tier-check, health-sentinel, usage-tracker
Tier 2 (Learning): {active/inactive} correction-detector, delegation-enforcer, session-summary
Tier 3 (Deep): {active/inactive} thinking-recall, auto-archival, precompact-extract
Usage (this session):
Tool calls: {from usage.json}
Top tools: {top 3 by count}
Memory:
Active project: {name or "none"}
Sessions tracked: {count of session files}
Plans: {count of plan files}
Data Sources
- Session count:
${CLAUDE_PLUGIN_ROOT}/_memory/.session-count - Tier: Calculated from session count (1: 0+, 2: 3+, 3: 10+)
- Experiences: Count files in
_memory/experiences/and_memory/experiences/_prewarmed/ - Usage: Read
${CLAUDE_PLUGIN_ROOT}/_memory/analytics/usage.json - Project: Read
${CLAUDE_PLUGIN_ROOT}/_memory/index.json
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.
- 2d ago First seen · 37 lines · 11 tokens per session scan A e1addd4629dc
context-stats is a command published in the GitHub repository primeline-ai/evolving-lite (48 stars, last pushed 15d ago), licensed MIT. It adds 11 tokens to every session and 316 once invoked, about $0.0001 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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