addlightness-bench — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited addlightness-bench (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.
Time two runnable commands head-to-head and report whether the difference is real -- not just noise. This is the measurement half of addlightness; it does not trim code (/addlightness) and does not measure static weight (/addlightness-review).
a significance verdict.
/addlightness. Ifthey want code-weight numbers (LOC/complexity), point them at /addlightness-review.
The user supplies two runnable commands: a before command and an after command. Read trailing args / the request as exactly that pair.
the command that runs each -- e.g. node old.js vs node new.js, python3 before.py vs python3 after.py.
comparison is meaningless. State the assumption if you have to guess.
Call the benchmark harness once:
"${CLAUDE_PLUGIN_ROOT}/scripts/benchmark.sh" \
--runs 10 --warmup 3 \
--before '<before-command>' \
--after '<after-command>'It uses hyperfine when present and falls back to a date+awk timing loop when it is not (this plugin assumes neither hyperfine nor any other profiler is installed, so expect the fallback). It prints one JSON line -- parse that, do not eyeball stdout. The emitted keys are exactly: before_ms, after_ms, pct_change (negative = after faster), faster (bool), welch_t, significant_at_95 (bool), runs, warmup, and tool. The harness does not compute median/p95/stddev -- do not expect or report those, even under hyperfine.
Report a compact table, then a one-line verdict:
| metric | value |
|---|---|
| before mean (ms) | before_ms |
| after mean (ms) | after_ms |
| % change | pct_change |
| welch t | welch_t |
| significant at 95% | significant_at_95 |
pct_change) -- negative means faster (after took less time).State it as "X% faster" / "X% slower" so the sign is unambiguous.
significant_at_95bool. The harness flags significance via a Welch t-test against a df-aware two-tailed 95% Welch critical value (emitted as t_crit_95; ~2.1-2.3 at the default N=10), NOT a fixed 1.96 — never recompute the verdict yourself.
significant_at_95 is true -> report the speedup/regression as real.the observed delta is within run-to-run noise." Do not* dress up a noise-level delta as a win. A faster-looking mean with significant_at_95 false is not a result.
For the numbers to mean anything:
not at different times of day.
stats.
contention dwarfs small deltas.
node x.js /python3 x.py includes interpreter startup, which has large jitter. If the stddev is on the order of the mean difference, the signal is swamped -- recommend more runs (25-30+) and/or moving the measured work in-process rather than per-invocation.
one -- rerun both together.
no win.
state, background load, and CPU governor drift invalidate the comparison.
the same result, a timing delta is meaningless -- flag it, don't report it.
/addlightness.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.