browse-tests-cbb1cb — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited browse-tests-cbb1cb (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
$VENV_PYTHON -c "
import json
from collections import Counter
cfg = json.load(open('.longmemeval-benchmarks/config.json'))
items = json.load(open(cfg['datasetPath']))
print(f'Variant: {cfg[\"datasetVariant\"]} Path: {cfg[\"datasetPath\"]} n={len(items)}')
c = Counter(i['question_type'] for i in items)
for qt, n in sorted(c.items()):
print(f' {qt:<28} {n}')
"| Argument | Default |
|---|---|
<question_id> | none — if omitted, list first 20 question_ids + types |
--max-sessions | 3 |
$VENV_PYTHON -c "
import json, sys
cfg = json.load(open('.longmemeval-benchmarks/config.json'))
items = json.load(open(cfg['datasetPath']))
qid = '<QUESTION_ID>'
it = next((x for x in items if x['question_id'] == qid), None)
if not it:
print('not found'); sys.exit(1)
print('question_type :', it['question_type'])
print('question :', it['question'])
print('answer :', it['answer'])
sessions = it.get('haystack_sessions') or []
print(f'sessions : {len(sessions)}')
for idx, s in enumerate(sessions[:3]):
print(f'--- session {idx+1} ({len(s)} turns) ---')
for t in s[:4]:
c = (t.get('content') or '')[:200]
print(f' [{t.get(\"role\")}] {c}')
"Always end with one-line dataset summary so the user knows what's loaded. Never dump entire sessions — the _s variant is 115k tokens per item.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.