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 skills/ozmasterai/torus-framework/benchmarknpx skills add OZmasterAI/Torus-Framework --skill benchmarkgit clone --depth 1 https://github.com/OZmasterAI/Torus-FrameworkWhat 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 | $0.00059 | $0.02993 |
| Opus 5 | $0.00030 | $0.01496 |
| Sonnet 5 | $0.00012 | $0.00599 |
| Haiku 4.5 | $0.00006 | $0.00299 |
Grade B, and why
benchmark scanned grade B with 2 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat ~/.claude/stats-cache.json Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run( How it starts
The opening of the file, as written. The whole thing — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/benchmark — Framework Performance Benchmarking
When to use
When the user says "benchmark", "measure performance", "track metrics", "how fast are the gates", "regression check", "baseline", or wants to quantify framework health over time.
Commands
/benchmark— Full benchmark run (measure + baseline + profile + analyze + report + save)/benchmark --quick— Skip profiling (measure + baseline + report only, faster)/benchmark --profile-only— Skip baseline comparison, run timing tests only/benchmark --save-only— Save current state as a new baseline without running profiling
Steps
1. MEASURE — Collect current metrics
Gather the following metrics from live framework state:
Test suite:
python3 ~/.claude/hooks/test_framework.py 2>&1 | tail -10
Extract: total tests, pass count, fail count, pass rate %.
Memory system:
cat ~/.claude/stats-cache.json
Returns: {"ts": <epoch>, "mem_count": <N>}. Also note memory count from search_knowledge("*", top_k=1) result header (total_memories field).
Framework state:
python3 -c "
import json
with open('~/.claude/LIVE_STATE.json') as f:
s = json.load(f)
print(json.dumps({
'session_count': s.get('session_count'),
'framework_version': s.get('framework_version'),
'feature': s.get('feature'),
}, indent=2))
"
Gate fire rates from today's audit log:
python3 -c "
import json, os, collections
from datetime import date
log = os.path.expanduser(f'~/.claude/hooks/audit/{date.today()}.jsonl')
if not os.path.exists(log):
print('No audit log for today')
else:
entries = [json.loads(l) for l in open(log) if l.strip()]
total = len(entries)
by_gate = collections.Counter(e.get('gate','?') for e in entries)
blocked = sum(1 for e in entries if e.get('decision') == 'block')
warned = sum(1 for e in entries if e.get('decision') == 'warn')
passed = sum(1 for e in entries if e.get('decision') == 'pass')
print(json.dumps({
'total_events': total,
'passed': passed,
'warned': warned,
'blocked': blocked,
'block_rate_pct': round(blocked/total*100, 1) if total else 0,
'top_gates': dict(by_gate.most_common(5)),
}, indent=2))
"
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 · 334 lines · 59 tokens per session scan B 6ed0b94a32c4
benchmark is a skill published in the GitHub repository OZmasterAI/Torus-Framework (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 59 tokens to every session and 2,993 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (reads agent configuration directories, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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