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Ssh Skill

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badseal
ssh-skill

Use when a task requires SSH or SCP/SFTP behavior, a remote server, server alias/IP/hostname/user@host, bastion or jump-host access, remote command execution, upload/download, server transfer, deployment, tunnels, port forwarding, or remote internal services; Chinese triggers include 服务器, 远程, 连接, 登录, 上传, 下载, 部署, 跳板机, 隧道. DO NOT use for local shell commands, localhost/current-machine work, local Docker, browser downloads, Git remotes, or direct non-SSH database access.

Overview

Publisherbadseal
Repositoryssh-skill
Skill namessh-skill
Stars
538
Forks
54
Bundled files
82
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 82 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by badseal on GitHub. Read the source before you install it.

Installation

Install the Ssh Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/badseal/ssh-skill/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/badseal/ssh-skill.git \
  .claude/skills/ssh-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ssh Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ssh Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ssh Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SSH Skill v4

Purpose

Use this contract for SSH-mediated work in Codex and Claude Code on Windows, macOS, and Linux. The deterministic Python CLI owns transport, retries, output limits, host-key policy, and compatibility behavior.

Chinese intent examples: 连接服务器, 远程执行, 上传文件, 下载日志, 通过跳板机, 建立隧道. Continue the user-facing conversation in the user's language.

Scope

Use for:

  • Commands or inspections on a remote host.
  • Upload, download, SFTP, SCP-equivalent, or server-to-server transfer.
  • SSH aliases, keys, agents, bastions, ProxyJump, tunnels, and port forwarding.
  • Remote deployment, remote database access through a tunnel, and cluster work.

DO NOT use for:

  • Local commands, localhost, current-machine services, or local Docker.
  • Browser or HTTP downloads that do not traverse SSH.
  • Git remote operations; use the relevant Git workflow instead.
  • Direct database connections that do not require an SSH tunnel.

Hard Rules

  1. Resolve the root containing this loaded SKILL.md; call it <SSH_SKILL_ROOT> for the current task.
  2. Invoke <SSH_SKILL_ROOT>/scripts/ssh_skill.py; do not construct raw ssh, scp, sftp, or rsync commands.
  3. Pass arguments as discrete process arguments. Never add a local shell wrapper around remote command text.
  4. Parse the one JSON document on stdout before deciding the next action.
  5. Treat outcome_unknown as a stop condition. Report its request ID and do not repeat the command automatically.
  6. Do not retry authentication failures, destructive commands, or partially completed multi-host operations without new evidence and user intent.
  7. Never expose passwords, private-key content, tokens, or askpass data.
  8. Preview multi-host and irreversible operations before applying them.

Resolve The Skill Root Once

  • Prefer the directory of the SKILL.md that activated this skill.
  • If the runtime provides an explicit loaded-skill path, use it directly.
  • Do not assume .agents, .codex, .claude, or any user-home path.
  • Run doctor --json when the root is ambiguous, a dependency is missing, or multiple installed copies may have drifted.
  • Do not run doctor before every operation. Reuse the resolved root within the same task unless the environment changes.
  • If doctor reports several copies, keep using the currently loaded copy and disclose version or content drift; never copy or overwrite automatically.

Read exactly one platform guide when invocation syntax is needed:

Standard Workflow

  1. Classify the request as exec, transfer, cluster, config, tunnel, or doctor.
  2. Resolve <SSH_SKILL_ROOT> once.
  3. Identify the SSH alias. If it is unknown, use config list-servers or config find; do not guess from an IP or a similar name.
  4. Separate read-only discovery from mutation. Ask for missing target or scope only when it materially changes the operation.
  5. Preview multi-host, production, delete, or overwrite work.
  6. Invoke the unified CLI once with the smallest complete operation.
  7. Parse success, data, error, and meta, then report the actual result.

Do not add connection tests, repeated status calls, or daemon restarts unless the result indicates that one of them is necessary.

Invocation Contract

Use the platform-appropriate Python executable and path syntax:

text
<PYTHON> "<SSH_SKILL_ROOT>/scripts/ssh_skill.py" <operation> <arguments>
  • Keep remote paths in POSIX form, such as /var/log/app.log.
  • Keep the entire remote command as one argument.
  • Prefer one remote command that gathers closely related read-only facts.
  • Keep dependent or separately risky mutations as separate operations.
  • Use --progress only when progress events are useful to the user.
  • Use --no-progress when a clean noninteractive stderr is required.

See references/commands.md for complete syntax.

Operations

OperationUse
execRun one command on one SSH alias.
uploadCopy a local file or directory to a remote POSIX path.
downloadCopy a remote file or directory to a local path.
transferMove data between two SSH aliases.
clusterPreview or apply one command to resolved host targets.
configList, find, create, update, delete, or export SSH aliases.
tunnelStart, list, inspect, or stop local SSH tunnels.
daemonInspect or manage the optional connection daemon.
doctorDiagnose local runtime, copies, OpenSSH, agent, and config.

Execution And Transfer

  • exec uses daemon reuse only where safe; --no-daemon is an explicit diagnostic escape hatch, not a routine first step.
  • A timeout after request transmission through OpenSSH, Paramiko, or cluster execution can mean the remote side executed the command. The CLI returns outcome_unknown with retryable=false; stop and ask the user how to verify state.
  • For upload/download, preserve the distinction between local native paths and remote POSIX paths. Use --recursive only for directories.
  • Use --resume when continuing a known interrupted transfer.
  • Server-to-server direct mode may expose an SSH agent to the source host. Agent forwarding remains off unless --allow-agent-forwarding is explicit.

Cluster And Configuration Gates

  • cluster without --apply is a target preview and opens no SSH connection.
  • Review targets, target_count, and production_targets from the preview.
  • Add --apply only after the requested target set is confirmed.
  • Add --confirm-production when any target is classified as production.
  • A config delete without --apply is a preview. Applied deletion creates a timestamped backup before atomic replacement.
  • Do not put new plaintext passwords into SSH configuration metadata.

Tunnels And Daemons

  • Return the allocated local port and tunnel ID after starting a tunnel.
  • Bind local forwarding only according to the tool's safe default.
  • Prefer status or list before stopping a tunnel when the identifier is vague.
  • Do not restart a daemon merely because a second command follows the first. The daemon is designed for reuse across compatible calls.

Result Contract

The CLI writes exactly one versioned JSON document to stdout:

  • schema_version: result schema, currently 1.0.
  • success: whether the requested operation completed successfully.
  • operation: stable operation identifier.
  • data: bounded operation-specific data.
  • error: stable code, message, retryability, and outcome on failure.
  • meta: request ID, platform, transport, elapsed time, and warnings.

The top-level stdout result is capped at 256 KiB. Recursive transfer details retain at most 100 head/tail samples while their total-count fields preserve the actual scale. Progress, when explicitly enabled, is real-time, bounded, ASCII-safe JSONL on stderr. Do not merge it with stdout. If output is truncated, disclose truncation and use the retained diagnostic tail instead of rerunning solely to obtain more output.

Safety Defaults

  • Host keys default to accept-new; changed known keys are rejected.
  • Do not disable host-key verification or discard known_hosts in routine use.
  • Existing legacy passwords may be read with warnings but must stay redacted.
  • Prefer keys and the platform SSH agent; never request a private key value.
  • Production and multi-host scope require observable confirmation flags.
  • Read references/safety.md before credential changes, production work, agent forwarding, config deletion, or uncertain outcomes.

Error Decisions

  • invalid_alias: list or find aliases once; do not brute-force names.
  • config_not_found: run doctor, then report the expected local config path.
  • Authentication failure: report the method and remediation; do not loop.
  • outcome_unknown: stop, preserve request ID, and verify state separately.
  • Partial cluster failure: report per-host outcomes; do not replay successes.
  • Missing dependency: use the relevant platform guide, not another shell.

Compatibility

  • Codex and Claude Code share this file and the same Python CLI.
  • Windows, macOS, and Linux share core behavior; only local invocation and dependency remediation differ.
  • Legacy script filenames remain compatibility entrypoints during v4 migration.
  • --legacy-json is only for an identified old consumer. New AI calls use the v1 envelope and never request legacy output.

Final Check

  • Correct loaded root and platform syntax used.
  • Correct alias, remote path, and target scope used.
  • Required preview and production confirmation completed.
  • One stdout JSON parsed; warnings and request ID preserved.
  • No secret exposed and no uncertain operation replayed.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 22 more files.

Frequently asked questions

What does the Ssh Skill AI skill do?

Use when a task requires SSH or SCP/SFTP behavior, a remote server, server alias/IP/hostname/user@host, bastion or jump-host access, remote command execution, upload/download, server transfer, deployment, tunnels, port forwarding, or remote internal services; Chinese triggers include 服务器, 远程, 连接, 登录, 上传, 下载, 部署, 跳板机, 隧道. DO NOT use for local shell commands, localhost/current-machine work, local Docker, browser downloads, Git remotes, or direct non-SSH database access.

Why use Ssh Skill on TypingMind?

Because you install it once and use it with any model. Ssh Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ssh Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/badseal/ssh-skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ssh Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ssh Skill?

As many as you like. As long as a model supports skills, you can use Ssh Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ssh Skill AI skill free?

It is published on GitHub by badseal. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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