python3 SKILL_DIR/scripts/check_compiled.py /abs/path/model.tflite [--expect-target Tensor_G5]

python3 SKILL_DIR/scripts/compile_model.py --print-install [--colab]

python3 -m venv ~/.venvs/litert-tensor && source ~/.venvs/litert-tensor/bin/activate
pip install --upgrade pip
export GOOGLE_TENSOR_SDK_BETA=/abs/path/litert_plugin_compiler.tar.gz   # from the Beta e-mail
pip install --no-cache-dir ai-edge-litert==<pinned> ai-edge-litert-sdk-google-tensor==<pinned>

undefined

The script prints the compilation report, re-verifies the Tensor stamp, writes
`<output>.compile.json` (flags, ops offloaded / total, package versions,
SHA-256s) and never overwrites an existing output (exit 2) unless
`--overwrite` is given. Ops left on the CPU in the report mean the strict NPU
benchmark will fail (step 3, `--allow-cpu-fallback`). Every compiler, script
and Colab option: [references/compile-flags.md](references/compile-flags.md).

*   If the compiler crashes with an internal error - or the user reports that it
    did with the defaults (no need to reproduce the crash) - use
    `--truncation-type half --sharding-intensity maximum` (public FAQ guidance)
    and tell the user which flags produced the artifact. `half` changes the
    numerics (16-bit floats on the TPU), so tell the user to validate the
    model's outputs against the original before relying on it.
*   Report a compile-only job from the script's output and sidecar only:

    ```markdown
    **Compiled:** <output path> (<bytes from "Compiled model written to" line>)
    **Target / flags:** <cli_flags from the sidecar, or "--target X (compiler defaults)">
    **Ops offloaded:** <N / M from the "Ops offloaded to the TPU" line>
    **LiteRT:** <"packages" from the sidecar, plus the script's WARNING/NOTE line if it printed one>
    **Verified:** check_compiled.py -> <its Status line>
    ```

Exit codes: 0 ok, 2 bad input, 3 already compiled, 4 unsupported host,
5 LiteRT packages or Beta compiler library missing (message includes the
install fix), 6 compile failed (compiler log errors are printed),
7 output verification failed.

python3 SKILL_DIR/scripts/benchmark_on_device.py \
  --model /abs/path/compiled/model_Google_Tensor_G5.tflite \
  [--cpu-baseline /abs/path/model.tflite] [--serial SERIAL] \
  [--dispatch-lib /abs/path/libLiteRtDispatch_GoogleTensor.so] \
  [--output-dir /abs/path/results]

**Summary:** <NPU "Inference avg" from the table> ms on the TPU vs <CPU "Inference avg"> ms on the CPU (<the N.NNx value from the script's "NPU speed-up vs CPU" line>); peak memory <NPU> vs <CPU> MB; <strict NPU | CPU fallback allowed>. TPU tile time <"TPU tile time / inference" row> ms per inference. TPU energy <"TPU energy / inference" row> mJ per inference.

<header and table exactly as printed by benchmark_on_device.py, including any "Unexpected log lines" section>

**Notes:** <what the Log check line reports: "none" when both logs show 0 unexpected lines and no profiler retry; otherwise each unexpected line with its meaning from references/benchmark-flags.md or troubleshooting.md, plus anything the user should validate>

**Not run:** <the script's ERROR line verbatim>

- Device: <the "Device: ..." line printed by benchmark_on_device.py, or the `adb devices -l` line>
- Model: <the "Status: ..." line from check_compiled.py>
- Nothing was pushed to or removed from the phone.

**Options:** <the next actions from step 1 / troubleshooting, most specific first>

undefined

1.  Run `check_compiled.py` on every file first (step 1), and package builds
    that passed the strict benchmark (step 3).
2.  Run with `--dry-run` first (any `python3`), then for real with a Python
    that has `ai-edge-litert`. The script refuses mismatched inputs and never
    replaces a directory it did not write.
3.  For 5b, show the user the verdict and the file list: `drop-in` (only
    model files change), `structural` (`UPDATE.md` section 2 lists the other
    changes; list them and ask how to proceed before anything else) or
    `up-to-date`. A `Runtime` check of `device` means the new builds must pass
    the strict benchmark with the app's own runtime library first (`UPDATE.md`
    section 4).
4.  Paste the script's `**Packaged:** ...` or `**Update plan:** ...` block
    verbatim, add one line (the delivery mode or the verdict in plain words,
    and "next: `<output-dir>/INTEGRATION.md`" or `UPDATE.md`), then ask: "The
    integration plan is ready (`INTEGRATION.md`). Do you want me to apply it
    to your project?" (or "The update plan is ready (`UPDATE.md`). ..."). If
    yes, go to step 6. Publishing to Google Play stays with the user.

Exit codes: 0 ok, 2 bad input (missing file, duplicate SoC, invalid name,
output exists, a build that differs from its sidecar, or a project
`--update-project` cannot update as is), 3 wrong model kind (uncompiled
`--compiled`, compiled `--fallback`), 5 LiteRT not importable or its exporter
API changed (the message has the fix), 7 post-export verification failed
(nothing is left at `--output-dir`).

python3 SKILL_DIR/scripts/install_and_verify.py --project /abs/path/to/app-project \
  [--app-module app] [--variant debug|release|<flavor>Debug] [--serial <id>] \
  [--uninstall-first] [--dry-run]