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 skills add google-ai-edge/litert-samples --skill litert-compiled-model-migrationgit clone --depth 1 https://github.com/google-ai-edge/litert-samplesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/google-ai-edge/litert-samples/litert-compiled-model-migration)<a href="https://agentmods.dev/skills/google-ai-edge/litert-samples/litert-compiled-model-migration"><img src="https://agentmods.dev/badge/skills/google-ai-edge/litert-samples/litert-compiled-model-migration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/google-ai-edge/litert-samples/litert-compiled-model-migration"><img src="https://agentmods.dev/badge/skills/google-ai-edge/litert-samples/litert-compiled-model-migration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00101 | $0.07961 |
| Opus 5.5 | $0.00040 | $0.03184 |
| Sonnet 5.5 | $0.00020 | $0.01592 |
| Haiku 4.5 | $0.00010 | $0.00796 |
Grade A, and why
litert-compiled-model-migration 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 20d 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: LiteRT Compiled Model Migration SKILL
Description
This skill guides an AI agent to rapidly migrate an Android application from legacy TensorFlow Lite (TFLite) to the modern LiteRT CompiledModel API (2.x) in Open Source GitHub repositories. It prioritizes a high-speed, 1st-pass "Like for Like" baseline migration with automated self-testing, and encourages advanced performance upgrades including off-main-thread execution with buffer reuse and NPU JIT compilation.
Read first: what the Kotlin CompiledModel API (com.google.ai.edge.litert, 2.3.0; 2.2.0 has the same API) has
CompiledModel.create(context.assets, assetName, CompiledModel.Options(Accelerator.CPU), env)andcreate(filePath, options, env);Optionstakes one or more ofAccelerator.CPU/GPU/NPU(e.g.Options(Accelerator.GPU, Accelerator.CPU));envisEnvironment.create(context)(optional; enables the compiler cache) orEnvironment.create(context, BuiltinNpuAcceleratorProvider(context))for the NPU. Nothing takes a ByteBuffer or a mapped file.- Buffers come from the model (
createInputBuffers()/createOutputBuffers(),List<TensorBuffer>;writeFloat(FloatArray)/writeInt8(ByteArray)/writeInt/writeLong,readFloat()and friends; create them once).run(inputs, outputs)is synchronous on the CPU; on the GPU it can return before the GPU finishes andread*()waits; there is no callback API.CompiledModel,TensorBufferandEnvironmentareAutoCloseable: close buffers, then the model, then anEnvironmentthe app created. CompiledModel.Options()with no accelerator compiles, butcreatethen throwsLiteRtException.Interpreter,GpuDelegate,NnApiDelegateand the Support library'sModel(com.google.ai.edge.litert.support.model.Model, which runs onInterpreterApi) do not appear in migrated code; the rest of LiteRT Support does, undercom.google.ai.edge.litert.support(Step 1), withorg.tensorflow.lite.DataTypeas the type its classes take. ThelitertAAR also containsorg.tensorflow.lite.Interpreter, so leftover Interpreter code compiles (all butsetUseNNAPI, which 2.x does not have) and the Stage 1 import check is what catches it.templates/LiteRtModel.ktcompiles against the 2.3.0 and the 2.2.0 artifacts; start from it.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 20d ago Changed · +1 lines · +22 tokens per session 10f459c63ea8
- 1mo ago Changed · +17 lines · +6 tokens per session b41d23f84c16
- 1mo ago Changed · +2 lines · -3 tokens per session 463647e7fb7e
- 1mo ago First seen · 195 lines · 76 tokens per session scan A a62d67083a9c
litert-compiled-model-migration is a skill published in the GitHub repository google-ai-edge/litert-samples (473 stars, last pushed yesterday), licensed Apache-2.0. It adds 101 tokens to every session and 7,961 once invoked, about $0.0004 per session on Opus 5.5. 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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