Agent skill

Wally Kit Pin

by RunanywhereAI in RunanywhereAI/wally

Bump cmake/sdk-pin.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock).

MITAuto-check passed

Install Wally Kit Pin

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

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

GitHub CLI
$ gh skill install RunanywhereAI/wally wally-kit-pin --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-kit-pin .claude/skills/wally-kit-pin && 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-kit-pin
GitHub stars
1.6k
Token cost
~1k tokens
SKILL.md length
379 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

Bump cmake/sdk-pin.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock).

  • Works in 3 steps: SDK GitHub Release v$SDK is published… → Public assets exist → Do not point WALLY_SDK_DIR at SDK source…
  • SKILL.md covers Preconditions, Bump together (never…, CI Swift tree and Private overlays, plus 1 more section
  • Calls bash, cmake and gh; needs GITHUB_TOKEN

What it does

Wally Kit Pin is an agent skill from RunanywhereAI/wally. Bump cmake/sdk-pin.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock). Use after an SDK GitHub Release is published (not draft), when fetch-kit.sh 404s, or when SCHEMALOCK mismatches.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with C++, GitHub and macOS. 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.

Example prompts

  • “/wally-kit-pin”

Requirements

  • A credential in GITHUB_TOKEN

Workflow steps

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

  1. SDK GitHub Release v$SDK is published (isDraft=false). Drafts 404
  2. Public assets exist
  3. Do not point WALLY_SDK_DIR at SDK source — configure error.

What it can do on your machine

Read from SKILL.md and the folder at commit 3819f46. 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

    Shell commands in SKILL.md call:

    • bash
    • cmake
    • gh

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

  • Network

    No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GITHUB_TOKEN

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

Context cost

Wally Kit Pin loads about 1k tokens when it runs. Until then it costs about 56 tokens; SKILL.md has 379 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~56
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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 3819f46, republished under its MIT licence (© RunanywhereAI). 379 words, ~1,009 tokens.

Download SKILL.mdSave it as .claude/skills/wally-kit-pin/SKILL.md (or your agent's skills folder).
name
wally-kit-pin
description
Bump cmake/sdk-pin.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock). Use after an SDK GitHub Release is published (not draft), when fetch-kit.sh 404s, or when SCHEMA_LOCK mismatches.

Wally kit pin

Pin file: cmake/sdk-pin.cmake. Fetcher: scripts/build/fetch-kit.sh. Overlay: scripts/build/fetch-private-pack.sh. CMake wrapper: cmake/RunAnywhereSDK.cmake.

Companion: cpp-desktop-kit in runanywhere-sdks (what the tarball contains).

Preconditions

  1. SDK GitHub Release v$SDK is published (isDraft=false). Drafts 404 for this repo's GITHUB_TOKEN. Prerelease is fine; latest is not required.
  2. Public assets exist: RunAnywhere-cpp-desktop-{macos-arm64,windows-x64}-v$SDK.tar.gz (+ windows-arm64 once that kit is on the release).
  3. Do not point WALLY_SDK_DIR at SDK source — configure error. Prefix is -DCMAKE_PREFIX_PATH= or -DWALLY_SDK_KIT=.

Bump together (never version-only)

bash
# After SDK v$SDK is published:
gh release download "v$SDK" --repo RunanywhereAI/runanywhere-sdks \
  --pattern 'RunAnywhere-cpp-desktop-*-v'"$SDK"'.tar.gz*' -D /tmp/kits
shasum -a 256 /tmp/kits/RunAnywhere-cpp-desktop-*.tar.gz

Update in cmake/sdk-pin.cmake:

  • WALLY_PINNED_SDK_VERSION
  • WALLY_PINNED_KIT_SHA256_MACOS_ARM64
  • WALLY_PINNED_KIT_SHA256_WINDOWS_X64
  • WALLY_PINNED_KIT_SHA256_WINDOWS_ARM64 (uncomment once the asset exists)
  • IDL triple copied from the kit's share/runanywhere/SCHEMA_LOCK: WALLY_PINNED_IDL_VERSION, WALLY_PINNED_IDL_SCHEMA_SHA256, WALLY_PINNED_IDL_PROTOC_VERSION

fetch-kit.sh refuses SDK_VERSION != WALLY_PINNED_SDK_VERSION. Do not override only an env var to "try" a newer kit — checksums are keyed to the pin.

Configure fails if the extracted kit's SCHEMA_LOCK does not match the IDL pin. When the schema changes, consume a new kit and bump the pin — never hand-write proto types locally. Wally never runs protoc: crate::io::proto::v1::* is generated at build time by prost/protox straight from the new kit's .proto files (build.rs), and nothing generated is committed.

src/sys/bindings.rs (the rac_* C ABI declarations) is committed and derived from the kit's C headers by bindgen — regenerate it after a kit pin bump with scripts/build/gen-sys-bindings.sh (--check verifies it is current; CI runs that on macOS).

Show full SKILL.md (169 more words)Show less

CI Swift tree

.github/workflows/ci.yml and release.yml check out RunanywhereAI/runanywhere-sdks at ref: v$SDK into .deps/runanywhere-sdks for the Apple MLX host (WALLY_SDK_SWIFT_PATH). Bump that ref in the same commit as the pin. macos-26 (Xcode 26 / Swift 6.2 — matches SDK swift-tools-version: 6.2); macos-15 is Swift 6.1; macos-14 is Swift 5.10.

Private overlays

Not part of the pin. Applied after extract:

  1. WALLY_PRIVATE_OVERLAY (local tarball)
  2. tarball next to the kit prefix named RunAnywhere-cpp-desktop-{macos-arm64-neurt,windows-arm64-qhexrt}-private-v*.tar.gz
  3. skip (OSS) unless WALLY_REQUIRE_PRIVATE=1

QHexRT is Windows ARM64 only. Public bottles must stay OSS — never bake overlay bytes into a Homebrew bottle or a public GitHub Release asset.

Windows ARM64 public kit is commons-only (no llama.cpp). Overlay apply then rebuild product wally.exe. v0.20.28 ARM64 kits are missing lib/libcurl.lib (packager only globbed x64-windows-static) — copy from vcpkg arm64-windows-static until the next SDK kit train. Wally cmake/RunAnywhereSDK.cmake links that import lib when present.

NeuRT: public mac bottle has MLX, not NeuRT. Overlay tarball + WALLY_APPLE_MLX_HOST=ON rebuild. See wally-e2e for QAIRT / SD15 / DSP gotchas; do not weaken public CI to require overlays.

Verify

bash
bash scripts/build/fetch-kit.sh macos-arm64 /tmp/kit
cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_PREFIX_PATH=/tmp/kit
cmake --build build -j "$(sysctl -n hw.logicalcpu)"
WALLY_SDK_KIT=/tmp/kit bash scripts/test/e2e.sh ./build/wally

© 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-kit-pin of RunanywhereAI/wally.

Open the folder on GitHubat commit 3819f46

Compare with similar skills

Wally Kit Pin 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 Kit Pin compared with similar skills
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Mole CLI Release Flowtw93/Mole70k—~2.6kAutomated safety check: PassGPL-3.0
Release Easydicttisfeng/Easydict15k—~810Automated safety check: PassGPL-3.0
pybind11 Release Publicationpybind/pybind1118k—~2.5kAutomated safety check: PassCustom licence
Cherry Studio Regression TestsCherryHQ/cherry-studio53k—~1.2kAutomated safety check: PassAGPL-3.0

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Works with

Questions about Wally Kit Pin

What does Wally Kit Pin do?

Bump cmake/sdk-pin.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock). Wally Kit Pin is an agent skill from RunanywhereAI/wally.cmake to a new published SDK C++ desktop kit (version + SHA-256 + IDL lock).

How do I install Wally Kit Pin in Claude Code?

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

How do I install Wally Kit Pin in Codex?

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

Can I use Wally Kit Pin 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-kit-pin -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-kit-pin, .gemini/skills/wally-kit-pin, .github/skills/wally-kit-pin and .opencode/skills/wally-kit-pin in your project.

What does Wally Kit Pin need to run?

Going by SKILL.md and its folder, Wally Kit Pin needs the command-line tools its instructions call (bash, cmake and gh) and credentials named GITHUB_TOKEN. Our summary lists: A credential in GITHUB_TOKEN.

Does Wally Kit Pin access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Wally Kit Pin 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 Kit Pin use?

Wally Kit Pin 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 Kit Pin use?

About 1k tokens (SKILL.md is roughly 4k 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 Kit Pin?

Skills that share tags, products or a category with Wally Kit Pin: Subspace Builds (dallison/subspace, 104 stars), Mole CLI Release Flow (tw93/Mole, 70k stars), Release Easydict (tisfeng/Easydict, 15k stars) and pybind11 Release Publication (pybind/pybind11, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wally Kit Pin?

RunanywhereAI (a GitHub organization) maintains it in RunanywhereAI/wally, which has 1,562 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 10, 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.