Agent skill

Wally E2E

by RunanywhereAI in RunanywhereAI/wally

Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows.

MITAuto-check passedTesting & QA

Install Wally E2E

skills CLI
$ npx skills add RunanywhereAI/wally --skill wally-e2e -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install RunanywhereAI/wally wally-e2e --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/RunanywhereAI/wally.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/wally-e2e .claude/skills/wally-e2e && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
wally-e2e
GitHub stars
1.6k
Token cost
~3.8k tokens
SKILL.md length
1,806 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows.

  • Works in 3 steps: The overlay-skel-files-never-shipped bug… → qhexrt::qnn::Backend::profile() — called… → Wally-specific, and NOT fixed by the…
  • CI smoke/e2e is red
  • SKILL.md covers What "green" means, backends must walk every live…, Windows DLLs and Apple MLX host link, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Wally E2E is an agent skill from RunanywhereAI/wally. Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows. Use when CI smoke/e2e is red, backends are missing, DLLs fail to load, or the Apple MLX host fails to link.

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering End-to-end testing. It works with C++, macOS and Qwen. The repository describes itself as: Get up and running with GLM-5.3-flash, DeepSeek, Gemma and other open source frontier models. The licence is MIT.

When your agent uses it

  • CI smoke/e2e is red
  • Backends are missing
  • DLLs fail to load
  • The Apple MLX host fails to link

Example prompts

  • “/wally-e2e”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. The overlay-skel-files-never-shipped bug (above), fixed upstream in
  2. qhexrt::qnn::Backend::profile() — called (via the same
  3. Wally-specific, and NOT fixed by the kit-pin bump alone

What it can do on your machine

Read from SKILL.md and the folder at commit 39b923e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Wally E2E loads about 3.8k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 1,806 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from RunanywhereAI/wally at commit 39b923e, republished under its MIT licence (© RunanywhereAI). 1,806 words, ~3,776 tokens.

Download SKILL.mdSave it as .claude/skills/wally-e2e/SKILL.md (or your agent's skills folder).
name
wally-e2e
description
Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows. Use when CI smoke/e2e is red, backends are missing, DLLs fail to load, or the Apple MLX host fails to link.

Wally e2e

Entry: scripts/test/e2e.sh <path-to-wally>. Always runs scripts/test/smoke.sh, then scripts/test/e2e-modalities.sh (engine-agnostic primitives). Public CI leaves modality knobs unset so every round-trip skips. Device runs set WALLY_E2E_<MOD> / WALLY_E2E_MODEL_ROOTS / WALLY_E2E_AUTO=1. See wally-device-e2e for ANE/NPU.

EnvPrimitiveExample
WALLY_E2E_LLM / WALLY_E2E_MODELllmmlx-qwen3 or a *_HNPU dir
WALLY_E2E_STTsttwhisper-tiny or whisper_base_HNPU
WALLY_E2E_TTSttspiper or kitten_micro_0_8_HNPU
WALLY_E2E_VLMvlmsmolvlm2 (SDK inserts the media marker)
WALLY_E2E_EMBEDembedminilm or embeddinggemma_300m_HNPU
WALLY_E2E_IMAGEimagecompiled SD1.5 tree / sd15
WALLY_E2E_NEURT_MODELclassified by pathsd15, a Parakeet ANE tree, or lfm2-230m-ane
WALLY_E2E_VADvadsilero
WALLY_E2E_RERANKrerankbge-reranker
WALLY_E2E_SEGMENTsegmentsegformer (P6 PPM)
WALLY_E2E_ENGINEoverride onlyqhexrt / neurt / mlx

Legacy WALLY_E2E_MLX_MODEL / WALLY_E2E_NEURT_MODEL / WALLY_E2E_QHEXRT_MODEL are classified by path/id into a primitive (not always image). Do not add new engine-named knobs.

scripts/test/assert-binary-backends.sh greps nm/llvm-nm/dumpbin/strings for registrar symbols (raMLXRegisterRuntime, rac_plugin_entry_neurt, rac_plugin_entry_qhexrt, …) so a backends() listing cannot pass without the engine actually being linked into the bottle.

Pass WALLY_SDK_KIT so overlay backends (neurt / qhexrt) are required when those libs are in the kit. CMAKE_PREFIX_PATH is only used for HAS_* flags and Windows DLL staging — an ambient overlay prefix must not make a public OSS bottle fail for missing NeuRT.

What "green" means

scripts/test/assert-backends.sh requires every engine the kit actually ships:

ConditionRequired wally --json backends name
no kit Config (public OSS bottle)llamacpp + onnx + sherpa
kit RunAnywhere_HAS_LLAMACPP TRUEllamacpp
kit RunAnywhere_HAS_ONNX TRUEonnx
kit RunAnywhere_HAS_SHERPA TRUEsherpa
Darwin arm64 product binary wally (not wally-cxx)mlx
overlay lib/librac_backend_neurt.a / rac_backend_neurt.libneurt
overlay lib/librac_backend_qhexrt.a / rac_backend_qhexrt.libqhexrt

Do not drop sherpa from the expected list to make 0.20.26 Windows green while HAS_SHERPA is TRUE. That kit compiled sherpa with speech ops off (RAC_SHERPA_ROUTABLE=0): rac_backend_sherpa_register() returned SUCCESS, capability_check returned BACKEND_UNAVAILABLE, the registry refused the plugin. The fix is pin a routable kit (0.20.28+), not weaken the assertion.

backends must walk every live primitive

src/commands/cmd_backends.rs iterates 1 .. RAC_PRIMITIVE_COUNT-1, skipping retired wire value 6. ONNX without RAG only advertises SEGMENT / DIARIZE. A hardcoded GENERATE_TEXT / TRANSCRIBE / EMBED list made onnx invisible even when the plugin was registered. Do not reintroduce a primitive allow-list.

Windows DLLs

Win32 LoadLibrary searches the exe directory, then PATH. e2e.sh copies third_party / bin / lib *.dll next to wally.exe and prepends those dirs to PATH before smoke. Skipping that produces "llamacpp only" even when the kit contains rac_backend_onnx.lib + onnxruntime.dll.

Never pass onnxruntime.dll to link.exe (LNK1107) — link the import lib; stage the DLL at runtime.

GitHub Windows: GITHUB_WORKSPACE is D:\a\...; msys tar -C needs cygpath -u (fetch-kit.sh already does).

cmake/WallyRust.cmake gets the kit's link line without hand-parsing Ninja: it queries the CMake file API (cmake_file_api(QUERY API_VERSION 1 CODEMODEL 2)) against wally_link_probe, a target configured but never built that carries the same kit closure the old C++ wally executable had. build.rs (link_native/probe_link_args) reads that reply, drops compile-only fragments (-D/-I/-O/…), hands the rest to cargo as rustc-link-args for every artifact it links, and — when WALLY_NATIVE_LINK_ARGS_OUT is set (CMake sets it) — writes the same list to build/wally-native-link-args.txt. scripts/build/build-mlx.sh reads that file and turns each fragment into an xcodebuild OTHER_LDFLAGS token, then links build/cargo/release/libwally.a (the crate's staticlib, built with the same fragments) against it. No manual ninja -t commands harvesting, no bundle-core.sh merge step — both are gone.

  • swiftc (Xcode 27) rejects raw -Wl, options and ignores bare archive paths in OTHER_LDFLAGS, so build-mlx.sh sends everything aimed at ld through -Xlinker; -l/-L/-F and -framework are swiftc options and pass through as-is.

scripts/build/build-mlx.sh must dump the xcodebuild log on failure (Undefined symbols does not contain error:). Do not grep bare error: — every CompileC line contains -Werror=. Observed CI 32786359915: grep error:|Metal|BUILD left only clang: error: linker command failed.

Never put # comments in a \-continued xcodebuild invocation. Bash cuts the command there, so OTHER_LDFLAGS and the log redirect never run (empty xcodebuild-mlx.log, status taken from a later assignment).

Link flags that must survive the Swift host:

  • The kit's plugin backends (static registrars) arrive already force-loaded in the fragments CMake recorded for wally_link_probe — build-mlx.sh does not re-derive which archives need -force_load, it replays what CMake linked.
  • -L$KIT/third_party -lonnxruntime and -Wl,-rpath,$KIT/third_party must both survive the flag rewrite, or the Swift host abort-traps at launch (Library not loaded: @rpath/libonnxruntime.dylib).
  • The crate's own native dependencies (Rust std, native-tls's Security.framework, -liconv) and the C++ runtime (-lc++, the kit links through the C++ driver) go on the link line after the kit's own flags (build-mlx.sh's rust_native array).
  • Canonicalize WALLY_SDK_SWIFT_PATH with cd && pwd. SwiftPM's local package identity is the directory name, so …/EXTERNAL/Wally/../.. registers as ... Nested checkouts named sdks1 must use that name in .product(..., package:).

Do not point WALLY_SDK_SWIFT_PATH at an unreleased Package.swift whose sdkVersion zips 404 (v0.20.28 before publish). CI checks out the tagged SDK tree (ref: v$SDK) whose binaryTargets already exist.

CI macOS runner is macos-26 (Xcode 26 / Swift 6.2). The MLX host resolves RunanywhereAI/runanywhere-sdks Package.swift, which is swift-tools-version: 6.2. macos-15 is Xcode 16.4 / Swift 6.1 and fails after a successful libtool merge with package 'runanywhere-sdks' is using Swift tools version 6.2.0 but the installed version is 6.1.0. macos-14 is Swift 5.10. release.yml must use the same runner as ci.yml.

Linux

Linux bottles are not a v1 merge blocker. Windows x64 and macOS arm64 are. scripts/test/e2e-linux.sh exists for later.

Private engines

NeuRT / QHexRT only appear in backends when the overlay was applied. scripts/test/e2e.sh requires neurt / qhexrt when lib/librac_backend_neurt.a or lib/rac_backend_qhexrt.lib exists — not by grepping packaged HAS_NEURT FALSE (that stays false; find_package flips it when the archive is present). Public CI must pass without overlays. Image gen (cmd_image.rs, gated #[cfg(wally_has_neurt)]) is compiled out unless NeuRT is present.

Show full SKILL.md (906 more words)Show less

Device / overlay gotchas (0.5.1 + kit 0.20.28)

Public bottles never list neurt or qhexrt. That is the product, not a test gap. Overlay-rebuild the product binary (WALLY_APPLE_MLX_HOST=ON on Mac; ARM64 MSVC + QHexRT overlay on Snapdragon).

  • CMAKE_PREFIX_PATH is not an overlay opt-in. Only WALLY_SDK_KIT makes e2e require neurt/qhexrt. An ambient overlay prefix from a previous rebuild will otherwise fail a public-bottle run.
  • Binary assert: never nm | grep -q under pipefail (SIGPIPE → false FAIL). Stream strings -a / nm -a. Darwin MLX proof is mlx-swift_Cmlx.bundle next to product wally (nm -gU misses Swift host symbols). First C++ rac_plugin_register(mlx) logs -811; Swift callbacks then register MLX — noisy, not a miss.
  • Windows ARM64 public/overlay kits have HAS_LLAMACPP FALSE. Do not require llamacpp in e2e. Overlay wally.exe listing only qhexrt (priority 150) is correct. On-disk GGUF (qwen3.5-2b) cannot run there.
  • QHexRT generate needs QAIRT matching the device skel, not the overlay DLL set. Snapdragon X2 Elite / Hexagon v81: QNN_SDK_ROOT + ADSP_LIBRARY_PATH=%QNN_SDK_ROOT%\lib\hexagon-v81\unsigned, copy aarch64-windows-msvc QnnHtp.dll / QnnHtpPrepare.dll / QnnHtpV81Stub.dll / QnnHtpV81CalculatorStub.dll / QnnSystem.dll next to wally.exe. Overlay 2.47 DLLs vs device 2.41 skels fail; QAIRT 2.48 worked. Pass the *_HNPU directory (--engine qhexrt), not a GGUF. FastRPC openSession timeouts (~90s) then user-driver fallback are normal; a second generate while DSP is wedged fails with Skel failed to process context binary / 0x3ea — taskkill wally.exe and use a .bat with fully expanded ADSP_LIBRARY_PATH (nested %QNN_SDK_ROOT% in cmd /c "set A=…&& set B=%A%\…" does not expand).
  • VS on the ARM64 box may be 2026 / 18 Community, not 2022: C:\Program Files\Microsoft Visual Studio\18\Community\VC\Auxiliary\Build\vcvarsarm64.bat. CMake/Ninja live under VS CMake extensions; they are not on default PATH.
  • v0.20.28 Windows ARM64 public kit omits libcurl.lib. Copy from arm64-windows-static into the kit lib/ before linking (fixed in the SDK packager for the next kit; do not retag 0.20.28). Wally already links kit libcurl.lib when present.
  • Published product bottles: macOS wally-$V-macos-arm64.tar.gz, Windows x86_64 zip, Windows arm64 zip, and Linux x86_64 wally-$V-linux-x86_64.tar.gz. NPU (NeuRT/QHexRT) is overlay-only on any platform.
  • The private QHexRT overlay tarball used to ship zero skel files (only .dll/.lib, no .so/.cat) — rac-cli's own overlay build could not run qwen3.8-27b-1bit-npu (the Bonsai/Maple ternary decoder) out of the box; validating it required hand-copying librun_main_on_hexagon_skel.so
    • .cat in from the electron-qhexrt npm package as a workaround. Fixed in runanywhere-sdks' scripts/build/package-private-engine-overlay.sh (widened the copy filter and added a pass for dsp/win-arm64/). Wally itself never had the ADSP_LIBRARY_PATH bug the Electron binding had — fastrpc_win.cpp's exe_dir() fallback naturally resolves for wally.exe because dependent DLLs/skels are staged flat beside the executable by this repo's own packaging convention — but that protection is a property of the packaging layout, not of Wally's code, so it is not something to assume going forward. Always build a fresh overlay from the actual release script and run the ternary model against it after any SDK kit-pin bump that touches QHexRT — do not assume last time's manually-patched overlay is still representative of what a real user's overlay build produces.
  • The private overlay tarball must be EXTRACTED ON TOP OF kit/, merging into the same directory tree (overlay/bin/* → kit/bin/, overlay/lib/* → kit/lib/, overlay/include/* → kit/include/, overlay/share/... → kit/share/...) — never kept as a separate sibling overlay/ directory fed to CMake via a second CMAKE_PREFIX_PATH entry. wally_stage_windows_runtime_dlls() (cmake/RunAnywhereSDK.cmake) only ever copies from ${RunAnywhere_LIBRARY_DIR}/../bin — i.e. kit/bin — so a same-named overlay/bin sitting next to kit/ is silently never consulted. Worse, this fails completely silently: the build succeeds, wally.exe links, and wally backends --json returns {"backends":[]} with no error naming QHexRT at all (find_library-style detection in RunAnywhereSDK.cmake just doesn't find kit/lib/rac_backend_qhexrt.lib because it was never copied there). If a fresh overlay build reports zero backends, check this BEFORE suspecting the overlay tarball's contents.
  • qwen3.8-27b-1bit-npu's HostOpFailed had THREE compounding causes, found and fixed one at a time — a kit-pin bump to v0.20.31 alone was NOT enough; Wally needed its own additional fix (below) even with a perfectly merged overlay.
    1. The overlay-skel-files-never-shipped bug (above), fixed upstream in runanywhere-sdks' overlay packaging script.
    2. qhexrt::qnn::Backend::profile() — called (via the same engines/qhexrt/qhexrt_session.cpp this repo statically links, same as the Electron binding) to pick the v75/v79/v81 manifest directory before the manifest is even parsed — shared its device query with the code path that opens a real QNN HTP device, so the ternary decoder's host_only manifest paid for a live QNN device it never needed. Fixed in neurun v0.20.31 (Backend::profile() no longer shares ensure_device() with device()) — see that repo's qhexrt-profile-must-not-create-live-device KB finding.
    3. Wally-specific, and NOT fixed by the kit-pin bump alone: copy-overlay-dlls.cmake globbed *.dll only, so even a correctly merged overlay (per the bullet above) left the Bonsai skel's .so/ .cat sitting in kit/bin/ and NEVER staged next to wally.exe — the one place fastrpc_win.cpp's ADSP_LIBRARY_PATH ∪ exe_dir() search actually looks. Fixed by widening the glob to *.dll *.so *.cat. fastrpc_win.cpp's SET_PATH/GET_PATH both returning a non-zero rc (0x14/AEE_EUNSUPPORTED) is EXPECTED and HARMLESS on this driver (libcdsprpc 11.1.4 simply doesn't implement that control call — see that file's own header comment) — do not treat it as a symptom of anything. This was chased as a diagnostic signal once and wasted real device time; the only signal that matters is whether remote_handle64_open for the skel itself returns non-zero (0x80000406 = AEE_EUNABLETOLOAD, which that same file's header comment exhaustively catalogs the causes of — missing skel, missing/wrong/stale .cat, or — as this entry adds — the pair never being in the searched directory at all). Confirmed fixed end to end on a Snapdragon X2 Elite with all three fixes in place: wally run --engine qhexrt against qwen3.8-27b-1bit-npu opens the cDSP session and generates correctly ("The capital of France is Paris.", 0.105 tok/s, 12425 DSP linears).

© RunanywhereAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/wally-e2e of RunanywhereAI/wally.

Open the folder on GitHubat commit 39b923e

Compare with similar skills

Wally E2E next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Wally E2E compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Wally E2E this skillRunanywhereAI/wally1.6k—~3.8kAutomated safety check: PassMIT
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Cherry Studio Regression TestsCherryHQ/cherry-studio52k—~1.2kAutomated safety check: PassAGPL-3.0
Kane CLI Browser TestingLambdaTest/kane-cli247—~8.4kAutomated safety check: PassApache-2.0
tmux Real User TestingQwenLM/qwen-code28k—~2.3kAutomated safety check: PassApache-2.0
E2E Session Testst0012/cctop154—~727Automated safety check: PassMIT

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Works with

Categories

Questions about Wally E2E

What does Wally E2E do?

Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows. Wally E2E is an agent skill from RunanywhereAI/wally. Verify a built wally binary against a pinned C++ desktop kit on macOS and Windows.

When should I use Wally E2E?

Wally E2E fits situations like: CI smoke/e2e is red; backends are missing; DLLs fail to load; the Apple MLX host fails to link.

How do I install Wally E2E in Claude Code?

Run `npx skills add RunanywhereAI/wally --skill wally-e2e -a claude-code`. Or copy the skill folder (.agents/skills/wally-e2e in RunanywhereAI/wally) into .claude/skills/wally-e2e in your project. Claude Code loads it when a task matches its description.

How do I install Wally E2E in Codex?

Run `npx skills add RunanywhereAI/wally --skill wally-e2e -a codex`. Or copy the skill folder (.agents/skills/wally-e2e in RunanywhereAI/wally) into .agents/skills/wally-e2e in your project. Codex loads it when a task matches its description.

Can I use Wally E2E in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add RunanywhereAI/wally --skill wally-e2e -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wally-e2e, .gemini/skills/wally-e2e, .github/skills/wally-e2e and .opencode/skills/wally-e2e in your project.

What does Wally E2E need to run?

SKILL.md names no scripts, command-line tools or credentials: Wally E2E is instructions for the agent only.

Does Wally E2E access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Wally E2E safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Wally E2E use?

Wally E2E is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Wally E2E use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Wally E2E?

Skills that share tags, products or a category with Wally E2E: Qwen Code E2E Testing (QwenLM/qwen-code, 28k stars), Cherry Studio Regression Tests (CherryHQ/cherry-studio, 52k stars), Kane CLI Browser Testing (LambdaTest/kane-cli, 247 stars) and tmux Real User Testing (QwenLM/qwen-code, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wally E2E?

RunanywhereAI (a GitHub organization) maintains it in RunanywhereAI/wally, which has 1,564 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 8, 2026.

Source: RunanywhereAI/wally on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.