OpenLogi macOS Permissions Triage
AprilNEA/OpenLogi
Decides whether an OpenLogi device problem on macOS is a privacy-permission (TCC) problem, using agent log lines, and says which identity needs which grant.
A skill your agent uses when starting, supervising, debugging, holding open, or stopping any remote process over SSH that needs an operator-like interactive environment, a TTY, login-shell startup…
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-process --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/remote-observable-process .claude/skills/remote-observable-process && rm -rf skills-srcUse ~/.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/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .claude/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-processType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-process --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/remote-observable-process .agents/skills/remote-observable-process && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .agents/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-process --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/remote-observable-process .cursor/skills/remote-observable-process && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .cursor/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Mesh-LLM/mesh-llm.git --path .agents/skills/remote-observable-process--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-process --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/remote-observable-process .gemini/skills/remote-observable-process && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .gemini/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-processInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/remote-observable-process .github/skills/remote-observable-process && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .github/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Mesh-LLM/mesh-llm remote-observable-process --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mesh-LLM/mesh-llm.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/remote-observable-process .opencode/skills/remote-observable-process && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "remote-observable-process" agent skill from https://github.com/Mesh-LLM/mesh-llm/tree/main/.agents/skills/remote-observable-process into .opencode/skills/remote-observable-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "remote-observable-process", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
remote-observable-processA skill your agent uses when starting, supervising, debugging, holding open, or stopping any remote process over SSH that needs an operator-like interactive environment, a TTY, login-shell startup…
Remote Observable Process is an agent skill from Mesh-LLM/mesh-llm. Use this skill when starting, supervising, debugging, holding open, or stopping any remote process over SSH that needs an operator-like interactive environment, a TTY, login-shell startup files, long-running observation, logs, readiness checks, or later inspection.
Its SKILL.md is about 560 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 Development, covering Debugging. It works with macOS. 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.
Read from SKILL.md and the folder at commit 2b36552. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
sshFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use ssh, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Remote Observable Process loads about 561 tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 246 words of instructions outside code blocks.
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.
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.
The full file from Mesh-LLM/mesh-llm at commit 2b36552, republished under its Apache-2.0 licence (© Mesh-LLM). 246 words, ~561 tokens.
.claude/skills/remote-observable-process/SKILL.md (or your agent's skills folder).Use this skill before starting a non-trivial remote process over SSH when the process needs to behave like it was launched by an operator in a terminal, be observed after launch, expose readiness, keep running beyond one command, or be stopped cleanly later.
If a macOS same-LAN join or split fails, or remote macOS nodes on the same LAN
connect only via relay, check the deploy-macos skill's Local Network
troubleshooting section before diagnosing iroh (not a routine preflight;
SSH/shell launches normally just work). A raw UDP probe, a
LAN address in an invite, or relay connectivity is not proof that the deployed
process was authorized. Do not collect performance data until both nodes report
the intended LAN peer as an iroh direct path.
For environment-sensitive processes, prefer SSH with a TTY and an interactive login shell:
ssh -tt host '/bin/zsh -ilc '\''COMMAND'\'''If the remote host does not use zsh, adapt the shell while preserving the same properties: allocate a TTY, use a login/interactive shell, and keep the session foreground for first repro/debug runs.
Avoid detached first attempts such as:
ssh host "nohup COMMAND > /tmp/process.log 2>&1 &"
ssh host "COMMAND > /tmp/process.log 2>&1 &"Those shapes hide lifecycle and can behave differently from a real remote session.
For network-sensitive server chains, model stage servers, GPU/Metal workloads, or bind/connect debugging, first prove the process in a held foreground TTY:
ssh -tt host '/bin/zsh -ilc '\''COMMAND 2>&1 | tee /tmp/COMMAND.log'\'''Keep the SSH session open while sending traffic. Use tmux or screen only
after validating that they preserve the same listener, downstream connection,
and request behavior on that host.
© 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
Just SKILL.md in .agents/skills/remote-observable-process of Mesh-LLM/mesh-llm.
Open the folder on GitHubat commit 2b36552
Remote Observable Process 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Remote Observable Process this skillMesh-LLM/mesh-llm | 3.5k | — | ~561 | Automated safety check: Pass | Apache-2.0 | |
| OpenLogi macOS Permissions TriageAprilNEA/OpenLogi | 23k | — | ~2.5k | Automated safety check: Notes | Apache-2.0 | |
| Cmux Debugging Guidemanaflow-ai/cmux | 28k | 1 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Gearcoleco Debuggingdrhelius/Gearcoleco | 141 | — | ~3.5k | Automated safety check: Pass | GPL-3.0 | |
| OpenLogi Device DiagnosisAprilNEA/OpenLogi | 23k | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| App Screenshot Debugtermio-sh/termio | 540 | — | ~1.2k | Automated safety check: Pass | MIT |
AprilNEA/OpenLogi
Decides whether an OpenLogi device problem on macOS is a privacy-permission (TCC) problem, using agent log lines, and says which identity needs which grant.
manaflow-ai/cmux
Covers debug logging, the Debug menu, profiling rules and runtime pitfalls for working on the cmux macOS terminal app.
drhelius/Gearcoleco
Debug and trace ColecoVision and Super Game Module games using the Gearcoleco emulator MCP server.
AprilNEA/OpenLogi
Finds the first failing layer when an OpenLogi Logitech device is missing or misbehaving across enumeration, open, probe, IPC and UI.
termio-sh/termio
Drive the running termio app via AppleScript / System Events to reach a UI state (focus the window, click a sidebar project, a terminal pane, a control), capture a pixel-accurate screenshot of just…
novotnyllc/dotnet-artisan
Debugs Windows and Linux/macOS applications (native, .NET/CLR, mixed-mode) with WinDbg MCP (crash dumps, !analyze, !syncblk, !dlk, !runaway, !dumpheap, !gcroot, BSOD), dotnet-dump, lldb with SOS…
Mesh-LLM/mesh-llm
A skill your agent uses when validating a MeshLLM release candidate or current HEAD against the last GitHub release, assembling the canonical feature/fix/modification inventory, testing locally…
Mesh-LLM/mesh-llm
A skill your agent uses when running, debugging, interpreting, or documenting mesh-llm benchmark tune model-serving throughput trials, including choosing…
Mesh-LLM/mesh-llm
A skill your agent uses when adding, renaming, removing, validating, or exposing mesh-llm config settings, including built-in settings, plugin config schemas, owner-control apply behavior, CLI…
Mesh-LLM/mesh-llm
A skill your agent uses when connecting agent tools or OpenAI clients to mesh-llm — launching or configuring Goose, Claude Code, OpenCode, Pi, curl, or any OpenAI-compatible client against a local…
Mesh-LLM/mesh-llm
A skill your agent uses when converting Hugging Face SafeTensors checkpoints into split BF16 GGUF model repos with skippy-quantize on Hugging Face Jobs or a local machine, then publishing the…
Mesh-LLM/mesh-llm
A skill your agent uses when creating, monitoring, validating, or documenting low-memory Hugging Face Jobs or local runs that quantize split BF16/FP16 GGUF model repos into custom quant GGUF repos…
Works with
Categories
A skill your agent uses when starting, supervising, debugging, holding open, or stopping any remote process over SSH that needs an operator-like interactive environment, a TTY, login-shell startup…. Remote Observable Process is an agent skill from Mesh-LLM/mesh-llm. Use this skill when starting, supervising, debugging, holding open, or stopping any remote process over SSH that needs an operator-like interactive environment, a TTY, login-shell startup files, long-running observation, logs, readiness checks, or later inspection.
Remote Observable Process fits situations like: stopping any remote process over SSH that needs an operator-like interactive environment; login-shell startup files; long-running observation; readiness checks.
Run `npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a claude-code`. Or copy the skill folder (.agents/skills/remote-observable-process in Mesh-LLM/mesh-llm) into .claude/skills/remote-observable-process in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Mesh-LLM/mesh-llm --skill remote-observable-process -a codex`. Or copy the skill folder (.agents/skills/remote-observable-process in Mesh-LLM/mesh-llm) into .agents/skills/remote-observable-process in your project. Codex loads it when a task matches its description.
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 remote-observable-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/remote-observable-process, .gemini/skills/remote-observable-process, .github/skills/remote-observable-process and .opencode/skills/remote-observable-process in your project.
Going by SKILL.md and its folder, Remote Observable Process needs the command-line tools its instructions call (ssh).
SKILL.md contains no URLs. Its commands use ssh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Remote Observable Process 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.
About 561 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Remote Observable Process: OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars), Cmux Debugging Guide (manaflow-ai/cmux, 28k stars), Gearcoleco Debugging (drhelius/Gearcoleco, 141 stars) and OpenLogi Device Diagnosis (AprilNEA/OpenLogi, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Mesh-LLM (a GitHub organization) maintains it in Mesh-LLM/mesh-llm, which has 3,484 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 7, 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.