matlab-profilelisted
Install: claude install-skill richardkmichael/claude-rodin
# MATLAB Performance Investigation
Investigate performance problems in the user's MATLAB code. The profiler is a
diagnostic tool — choose the right options and passes based on what you are
trying to learn. Iterate to build a complete picture, then report findings.
Do the investigation; the user decides what to change.
Read `${CLAUDE_SKILL_DIR}/references/PROFILER_REFERENCE.md` at the start of
every investigation for profiler options, output struct schema, and
interpretation rules.
## Tools
All scripts are in `${CLAUDE_SKILL_DIR}/scripts/`. Invoke them directly; they
are executable.
Analysis (take `profile.json`):
- `rank_functions.py <profile.json> [--top N] [--by time|memory|calls]`
- `line_breakdown.py <profile.json> [<function>] [--top N] [--lines M]`
- `compare_runs.py <before.json> <after.json> [--top N]`
MATLAB-side helpers (inline into `matlab -batch` commands or run via
`matlab -batch "run('...'); ..."`):
- `export_profile_json.m` — function `export_profile_json(info, outPath)`,
serialises `profile('info')` to JSON.
- `history_query.m` — function `events = history_query(matPath[, fnNames])`,
flattens FunctionHistory for call-pattern analysis.
Documentation lookup: use the `matlab-docs` skill when an unfamiliar
function appears in results.
## Constraints
- Do NOT optimize or refactor the user's code. The skill profiles and reports;
the user decides what to change. Temporary instrumentation (profiler guards,
tic/toc, input-capture saves for snapshot-and