Agent skill

Llama Stage Patch Changes

by Mesh-LLM in Mesh-LLM/mesh-llm

A skill your agent uses when changing mesh-llm's patched llama.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or…

Apache-2.0Auto-check passedAI & LLM Engineering

Install Llama Stage Patch Changes

skills CLI
$ npx skills add Mesh-LLM/mesh-llm --skill llama-stage-patch-changes -a claude-code

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

GitHub CLI
$ gh skill install Mesh-LLM/mesh-llm llama-stage-patch-changes --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/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/llama-stage-patch-changes .claude/skills/llama-stage-patch-changes && 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
llama-stage-patch-changes
GitHub stars
3.5k
Token cost
~2.6k tokens
SKILL.md length
1,178 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when changing mesh-llm's patched llama.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or…

  • Changing mesh-llms patched llama.cpp Skippy ABI
  • SKILL.md covers Boundaries, Native Source Layout, Graph input capabilities and Native API documentation, plus 3 more sections
  • Calls cargo, git and python3
  • Model introspection

What it does

Llama Stage Patch Changes is an agent skill from Mesh-LLM/mesh-llm. Use this skill when changing mesh-llm's patched llama.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or patch queue.

Its SKILL.md is about 2.6k 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 AI & LLM Engineering, covering LLM inference and serving. It works with llama.cpp and Rust. The repository describes itself as: Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. The licence is Apache-2.0.

When your agent uses it

  • Changing mesh-llms patched llama.cpp Skippy ABI
  • Model introspection
  • Tensor filtering
  • Activation-frame execution

Example prompts

  • “/llama-stage-patch-changes”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 48bf685. 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:

    • cargo
    • git
    • python3

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

  • Network

    No URLs in SKILL.md. Its commands use git, 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 no API keys, tokens, secrets or passwords.

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

Context cost

Llama Stage Patch Changes loads about 2.6k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 1,178 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

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 Mesh-LLM/mesh-llm at commit 48bf685, republished under its Apache-2.0 licence (© Mesh-LLM). 1,178 words, ~2,611 tokens.

Download SKILL.mdSave it as .claude/skills/llama-stage-patch-changes/SKILL.md (or your agent's skills folder).
name
llama-stage-patch-changes
description
Use this skill when changing mesh-llm's patched llama.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or patch queue.
metadata.short-description
Maintain the llama.cpp Skippy patch queue

llama-stage-patch-changes

Use this skill when changing the Skippy staged-runtime ABI carried in skippy/llama_cpp/patches.

Boundaries

  • Keep durable llama.cpp-side changes in the ordered queue under skippy/llama_cpp/patches: top-level core patches first, model_support/series second, and generated/series last.
  • Keep the upstream pin in skippy/llama_cpp/upstream.txt.
  • Do not edit .deps/llama.cpp as the final artifact; regenerate the patch queue from commits.
  • Keep mesh orchestration, protocol compatibility, lifecycle, model management, and API status behavior in Rust.
  • Keep one functional boundary per patch. Patch numbers must be unique and contiguous within each queue lane.
  • Put family-specific model support in a focused model_support/ patch. Keep reusable staged-runtime machinery in the core lane and generated graph annotations in the generated lane.
  • Keep public ABI declarations separate from independently reviewable model lifecycle, loading, and package implementation changes.
  • The Skippy native ABI is an internal lockstep boundary, not a stable cross-version compatibility contract. It may change whenever the feature requires it; update the Rust FFI mirror and all callers in the same change.
  • Do not preserve old native ABI signatures for compatibility. Bump the ABI version when the boundary changes so mismatches are diagnosable, and make sure the shipped Rust side and native runtime are built from the same queue.
  • Do not add a terminal source-reorganization patch. A deliberate layout or ownership change must be represented in the recreated patches that own the affected capabilities.

Native Source Layout

  • include/skippy.h is an umbrella only. Put public C ABI declarations in standalone include/skippy/<capability>.h headers.
  • Put implementations in src/skippy/<capability>.cpp and private C++ declarations in narrowly named src/skippy/*.h headers.
  • Use snake_case capability names. Keep exported symbols prefixed with skippy_ and avoid generic helpers, utils, or expanded common modules.
  • src/skippy.cpp is retired. Extend the owning capability module and keep new implementation files below 1,000 lines.
  • Make every public header independently compilable as both C11 and C++17. Update explicit CMake source lists and installation rules with new modules.
  • Do not preserve retired source include paths unless the task explicitly asks for compatibility. Continue to version and mirror any binary ABI change.

Graph input capabilities

  • Derive planned input modes from what the graph can execute, not merely from allocated input tensors. Shared builders may allocate an embedding input that a particular model's metadata forbids using.
  • Carry capability declarations through both helper construction and direct input-bundle registration. Keep model restrictions at graph construction; do not add family-name dispatch to the generic planner.
  • When adding an input-mode profile, cover both an accepting synthetic model and a rejecting variant. Preserve the graph's existing rejection of invalid direct input while ensuring metadata-only planning never probes that mode.

Native API documentation

  • Treat Doxygen-style comments in include/skippy.h and include/skippy/*.h as the source of truth for the public API reference. Every public header and exported skippy_* function must have an adjacent @brief describing what it is used for.

  • When the public header surface changes, prepare the patched checkout and regenerate the website reference before finishing the change:

    bash
    scripts/prepare-llama.sh pinned
    python3 scripts/generate-skippy-api-doc.py
    python3 scripts/generate-skippy-api-doc.py --check
  • Commit mesh/website/src/docs/pages/skippy-api.md alongside the native queue change. The generated page must not be hand-edited, and its inventory must include every public header and exported function in the prepared checkout.

ABI PR documentation requirements

Every pull request that changes the Skippy ABI must include an explicit ABI inventory in the PR description. Do not describe a changed function signature as a newly added function.

The inventory must state, for each change:

  • the exact symbol or declaration name and its complete signature or field change;
  • whether it was added, changed, deprecated, deleted, or removed;
  • the public header containing the declaration;
  • the implementation source and Rust FFI mirror, when applicable;
  • the ABI version before and after the change;
  • why the change is required and what data or behavior it enables;
  • that backward compatibility with older native runtimes is intentionally not required, and that the Rust FFI mirror and callers were updated in lockstep;
  • the tests that exercise the native ABI boundary, including public-header compilation when a header changes.

Use this compact table in the PR description:

StatusSymbol/declarationPublic headerImplementation / mirrorReasonLockstep update
Changed / Added / Removedexact name and signatureinclude/skippy/<capability>.hsrc/skippy/<capability>.cpp; Rust FFI pathbehavior enabledRust mirror/callers updated; old ABI not supported

For a changed function signature, call out that it is an ABI change even when the symbol name is unchanged. List removed declarations explicitly as “none” when no functions or fields were deleted; this prevents reviewers from having to infer removals from a patch diff. Keep this inventory synchronized with the ABI version constants in include/skippy/common.h and the mirrors in skippy/crates/skippy-ffi/src/lib.rs. Do not add compatibility shims solely to support an older native runtime; the acceptance criterion is a synchronized Rust/native build and a clear version mismatch if the pieces are mixed.

Show full SKILL.md (405 more words)Show less

Local Flow

Prepare the pinned checkout and current patch queue:

bash
scripts/prepare-llama.sh pinned

For llama-side editing, work in .deps/llama.cpp or another llama.cpp checkout where commits can be named and inspected. Base the branch on the pinned upstream, then carry core stage ABI commits, model-support commits, and generated family commits in that order.

For an ordinary core capability change, emit one focused mail-format patch after the current top-level core lane. Do not rewrite unrelated entries or put the patch after model_support/ or generated shards:

bash
repo_root="$(pwd)"
llama_checkout="${LLAMA_CHECKOUT:-$repo_root/.deps/llama.cpp}"
last_patch="$(find skippy/llama_cpp/patches -maxdepth 1 -type f -name '*.patch' | sort | tail -n 1)"
last_number="${last_patch##*/}"
last_number="${last_number%%-*}"
next_number=$((10#$last_number + 1))
git -C "$llama_checkout" format-patch -1 \
  --start-number "$next_number" \
  --output-directory "$repo_root/skippy/llama_cpp/patches" HEAD

For a deliberate queue-boundary or source-layout change, rebuild the affected series from the pinned upstream instead. Create capability-owned commits in their intended order, place declarations and implementation in their final modules from the first patch that introduces them, and format the complete replacement series with contiguous numbering. Before replacing the durable queue, verify both of these invariants:

bash
# The reconstructed commit series has exactly the intended final tree.
git diff --exit-code <authoritative-final-commit> <reconstructed-series-head>

# No patch defers the structural change to the end of the series.
git log --reverse --oneline <pinned-upstream>..<reconstructed-series-head>

Move the old queue to an explicit temporary backup, generate the replacement into a fresh skippy/llama_cpp/patches directory, and retain the backup until clean application and native compilation pass. Never keep both series or duplicate patch numbers in the durable directory.

Validation

Validate patch application in a clean checkout:

bash
tmp_root="$(mktemp -d /tmp/mesh-llama.XXXXXX)"
trap 'rm -rf -- "$tmp_root"' EXIT
LLAMA_WORKDIR="$tmp_root/llama.cpp" scripts/prepare-llama.sh pinned
LLAMA_WORKDIR="$tmp_root/llama.cpp" \
  MESH_LLM_LLAMA_BUILD_ROOT="$tmp_root/build" \
  LLAMA_STAGE_BACKEND=cpu \
  LLAMA_STAGE_LINK_MODE=static \
  scripts/build-llama.sh
Re-pinning upstream

Advancing skippy/llama_cpp/upstream.txt can silently invalidate a patch that depends on upstream's ordering, not just its symbols. The queue still applies, everything compiles, and the behavior is broken. This happened with upstream 1269cb1, which moved check_tensor_dims ahead of buft_for_tensor and left the stage tensor filter running too late; split serving was broken on main because no test opened a real mid-stage artifact.

So on every re-pin, in addition to the checks above:

  • Read git log <old-pin>..<new-pin> -- src/llama-model-loader.* src/llama-model.* for changes to load order, not just to signatures the patches touch.
  • Prove the staged load path with a real artifact whose first block is not block 0. cargo test -p skippy-package-builder covers this via mid_stage_artifact_opens_with_the_stage_filter_applied.
  • Confirm that test actually ran rather than skipped. It is gated on SKIPPY_CORRECTNESS_MODEL; without it the test prints skipping mid-stage: SKIPPY_CORRECTNESS_MODEL is not set and passes. Grep the CI log for mid_stage_artifact_opens_with_the_stage_filter_applied ... ok, or set the variable locally. A skipped gate reads identically to a pass.

Compile each new public header once as C11 and once as C++17 with warnings treated as errors. For implementation moves, run the tests owned by the moved capability in addition to the Rust fallout checks below.

For Rust fallout, run cargo commands serially:

bash
cargo fmt --all --check
cargo check -p mesh-llm
cargo test -p skippy-runtime --lib
cargo test -p skippy-serving --lib
cargo test -p mesh-llm --lib

Patch files are mail-format artifacts. Do not hand-normalize them in a way that breaks git am.

© Mesh-LLM, Apache-2.0. 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/llama-stage-patch-changes of Mesh-LLM/mesh-llm.

Open the folder on GitHubat commit 48bf685

Compare with similar skills

Llama Stage Patch Changes 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.

Llama Stage Patch Changes compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Llama Stage Patch Changes this skillMesh-LLM/mesh-llm3.5k—~2.6kAutomated safety check: PassApache-2.0
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Test Modelguoqingbao/xinfer333—~2.6kAutomated safety check: PassMIT
Aider DelegateamElnagdy/delegate-skills2.3k3 repos~3kAutomated safety check: PassMIT
Qwen Mtp GgufR6410418/Jackrong-llm-finetuning-guide1.7k—~1.7kAutomated safety check: PassMIT
Quantizationvllm-project/vllm-omni7.1k—~1.4kAutomated safety check: PassApache-2.0

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Works with

Questions about Llama Stage Patch Changes

What does Llama Stage Patch Changes do?

A skill your agent uses when changing mesh-llm's patched llama.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or…. Llama Stage Patch Changes is an agent skill from Mesh-LLM/mesh-llm.cpp Skippy ABI, runtime hooks, model introspection, tensor filtering, activation-frame execution, GGUF writer surface, upstream pin, or patch queue.

When should I use Llama Stage Patch Changes?

Llama Stage Patch Changes fits situations like: changing mesh-llms patched llama.cpp Skippy ABI; model introspection; tensor filtering; activation-frame execution.

How do I install Llama Stage Patch Changes in Claude Code?

Run `npx skills add Mesh-LLM/mesh-llm --skill llama-stage-patch-changes -a claude-code`. Or copy the skill folder (.agents/skills/llama-stage-patch-changes in Mesh-LLM/mesh-llm) into .claude/skills/llama-stage-patch-changes in your project. Claude Code loads it when a task matches its description.

How do I install Llama Stage Patch Changes in Codex?

Run `npx skills add Mesh-LLM/mesh-llm --skill llama-stage-patch-changes -a codex`. Or copy the skill folder (.agents/skills/llama-stage-patch-changes in Mesh-LLM/mesh-llm) into .agents/skills/llama-stage-patch-changes in your project. Codex loads it when a task matches its description.

Can I use Llama Stage Patch Changes 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 Mesh-LLM/mesh-llm --skill llama-stage-patch-changes -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llama-stage-patch-changes, .gemini/skills/llama-stage-patch-changes, .github/skills/llama-stage-patch-changes and .opencode/skills/llama-stage-patch-changes in your project.

What does Llama Stage Patch Changes need to run?

Going by SKILL.md and its folder, Llama Stage Patch Changes needs the command-line tools its instructions call (cargo, git and python3). Our summary lists: Python 3.

Does Llama Stage Patch Changes access the network?

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

Is Llama Stage Patch Changes 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 Llama Stage Patch Changes use?

Llama Stage Patch Changes is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Llama Stage Patch Changes use?

About 2.6k tokens (SKILL.md is roughly 10k 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 Llama Stage Patch Changes?

Skills that share tags, products or a category with Llama Stage Patch Changes: Add Model (guoqingbao/xinfer, 333 stars), Test Model (guoqingbao/xinfer, 333 stars), Aider Delegate (amElnagdy/delegate-skills, 2.3k stars) and Qwen Mtp Gguf (R6410418/Jackrong-llm-finetuning-guide, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Llama Stage Patch Changes?

Mesh-LLM (a GitHub organization) maintains it in Mesh-LLM/mesh-llm, which has 3,485 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 8, 2026.

Source: Mesh-LLM/mesh-llm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.