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/loopdive/js2/regression-triagenpx skills add loopdive/js2 --skill regression-triagegit clone --depth 1 https://github.com/loopdive/js2What 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 | $0.00072 | $0.02010 |
| Opus 5 | $0.00036 | $0.01005 |
| Sonnet 5 | $0.00014 | $0.00402 |
| Haiku 4.5 | $0.00007 | $0.00201 |
Grade A, and why
regression-triage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regression Triage
Given the regression artifact from a sharded test262 CI run, bucket the regressions by path prefix and error message pattern, sample each concentrated bucket to determine root cause, and classify as false positive, known gap, or real regression with a fix path.
When to use
- After a sharded run fails with N regressions but the net delta is positive (e.g. "+479 pass with 80 regressions")
- When you need to decide which regressions block a baseline commit vs which get filed as follow-ups
- When multiple merges could have introduced overlapping fails and you need to untangle them
Distinct from:
handle-regression— fixing a single specific regressionanalyze-regression— diffing two JSONL result files (that's step 1 here)
Step 1: Download the merged report artifact
mkdir -p output/regressions-$(date +%s)
gh run download <RUN_ID> -n test262-merged-report -D output/regressions-<TIMESTAMP>
Files: test262-report-merged.json, test262-regressions.txt, test262-results-merged.jsonl.
test262-regressions.txt only has summary stats. Extract the actual regression LIST by diffing the merged jsonl against the current baseline:
Step 2: Compute the regression list
The baseline JSONL is fetched on demand from loopdive/js2wasm-baselines
(#1528). Make sure the local cache is populated before diffing:
node scripts/fetch-baseline-jsonl.mjs
import json
base = {}
with open('.test262-cache/test262-current.jsonl') as f:
for line in f:
try:
d = json.loads(line)
base[d['file']] = d['status']
except: pass
new = {}
new_details = {}
with open('/tmp/regressions-<TS>/test262-results-merged.jsonl') as f:
for line in f:
try:
d = json.loads(line)
new[d['file']] = d['status']
new_details[d['file']] = d
except: pass
regressions = [(f, new.get(f, 'missing'), new_details.get(f, {}))
for f, s in base.items()
if s == 'pass' and new.get(f, 'missing') != 'pass']
print(f"Total: {len(regressions)}")
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 · 187 lines · 72 tokens per session scan A 5eeb385a282d
regression-triage is a skill published in the GitHub repository loopdive/js2 (59 stars, last pushed 2d ago), licensed Apache-2.0. It adds 72 tokens to every session and 2,010 once invoked, about $0.0004 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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