Iron Proxy Gateway for NanoClaw
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
Manage model API keys, default models and per-agent vault secrets with the penguin CLI.
$ npx skills add Prism-Shadow/penguin-harness --skill penguin-config -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Prism-Shadow/penguin-harness penguin-config --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/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .claude/skills/penguin-config && 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 "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .claude/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-configType 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 Prism-Shadow/penguin-harness --skill penguin-config -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Prism-Shadow/penguin-harness penguin-config --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .agents/skills/penguin-config && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .agents/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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 Prism-Shadow/penguin-harness --skill penguin-config -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Prism-Shadow/penguin-harness penguin-config --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .cursor/skills/penguin-config && 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 "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .cursor/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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/Prism-Shadow/penguin-harness.git --path plugins/agent-development/skills/penguin-config--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 Prism-Shadow/penguin-harness --skill penguin-config -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Prism-Shadow/penguin-harness penguin-config --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .gemini/skills/penguin-config && 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 "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .gemini/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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 Prism-Shadow/penguin-harness penguin-configInstalls 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 Prism-Shadow/penguin-harness --skill penguin-config -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .github/skills/penguin-config && 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 "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .github/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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 Prism-Shadow/penguin-harness --skill penguin-config -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Prism-Shadow/penguin-harness penguin-config --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/agent-development/skills/penguin-config .opencode/skills/penguin-config && 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 "penguin-config" agent skill from https://github.com/Prism-Shadow/penguin-harness/tree/main/plugins/agent-development/skills/penguin-config into .opencode/skills/penguin-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "penguin-config", 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.
penguin-configManage model API keys, default models and per-agent vault secrets with the penguin CLI.
Penguin Config is an agent skill from Prism-Shadow/penguin-harness. Manage model API keys, default models and per-agent vault secrets with the penguin CLI.
Its SKILL.md is about 2.3k 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 DevOps & Cloud, covering Secrets management. The repository describes itself as: 🐧 Unified and Stable RSI Platform. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit d56d9ce. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
Penguin Config loads about 2.3k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 1,079 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 Prism-Shadow/penguin-harness at commit d56d9ce, republished under its Apache-2.0 licence (© Prism-Shadow). 1,079 words, ~2,328 tokens.
.claude/skills/penguin-config/SKILL.md (or your agent's skills folder).The penguin CLI manages model credentials, default models and per-agent vault secrets. Its primary job is model configuration: penguin config model add registers a model, or — without --model-id — gives a whole group its key, base URL or protocol, and penguin config model list shows the groups' connections and the models currently available. Configuration goes through the CLI only — never read or hand-edit the underlying hidden files.
If the user's message only invokes this skill (e.g. "use penguin-cli skill") without a concrete request, ask the user what they want to configure. Do not run any command until the goal is clear.
Add or update a model (upsert by the (provider, model_id) pair; re-run with more options to amend an entry):
penguin config model add --provider <group> --model-id <upstream_id> [--api-key <key> | --clear-api-key] \
[--base-url <url> | --clear-base-url] [--client-type <type> | --clear-client-type] \
[--context-window <n>] [--max-tokens <n>] [--vision | --no-vision] [--fast-mode | --no-fast-mode] \
[--price-cache-read <n>] [--price-cache-write <n>] [--price-output <n>] \
[--project-id <id>] [--root <dir>] [--set-default](provider, model_id) pair, so --provider and --model-id are both required to name one — the group is never inferred from the model id, because gateways resell vendor models under their upstream ids and a wrong guess would send the key to another vendor's endpoint. --model-id takes the provider's upstream model id (what the API expects) and is persisted as the entry's request id, so it reaches the API unchanged; --provider names the group (deepseek, openai, anthropic, google, openrouter, siliconflow, … — custom for any other endpoint).custom, vllm, openrouter, tokendance, siliconflow and groups of your own take models added by hand. Every other built-in group carries its catalog models only: model add there accepts one of that group's catalog model ids (to set its key, limits or prices, or to bring it back) and refuses any other id with "cannot be added". Add such a model under custom with --base-url, or under a group of your own.--api-key, --base-url and --client-type set the model's own values, and --clear-api-key, --clear-base-url and --clear-client-type remove them. Omitted, the model follows its group (see Group connection), and with no group value it gets the client's default; the built-in catalog is never consulted. A model added to openrouter, tokendance or siliconflow needs only --provider and --model-id once the group has a key: a new Project already stores those gateways' endpoint and protocol on the group. For an OpenAI chat-completion compatible endpoint under custom or a group of your own, use --client-type openai --base-url <endpoint>, or set both once on the group; in a vendor group, omit --client-type to auto-route by model id.--vision / --no-vision mark whether the model accepts images; omitting both keeps the current value (default is vision-capable).--max-tokens <n> pins a per-model output cap (positive integer), overriding the Agent's model.max_tokens; omit to inherit. Lower it for small-context models — the per-Agent default (32000) cannot fit into e.g. a 32k context window together with any prompt.penguin config model ... and penguin config vault ... commands accept --root <dir> to target another data root (default PENGUIN_HOME, then ~/.penguin/data). Two configuration targets — treat the difference as a hard rule:--root <data root> as well — the parent directory of the App Data Dir named in your Environment section. An agent running inside PenguinHarness never sees PENGUIN_HOME: the harness strips every PENGUIN_* variable from a command's environment, so a command without --root falls back to ~/.penguin/data and configures a root the running server does not read.--root must point at the app's own data directory inside the project (e.g. --root ./penguin_data, the same path the app gives createAgent({ root })) unless the user explicitly chose another location — never write an app's models or keys into the global ~/.penguin/data, which belongs to the person running Penguin, not to the app.penguin config model list --root <app root> should show the app's entries, and the global list (no --root) should stay clean.Other model commands:
penguin config model default --model-id <upstream_id> --provider <group> [--root <dir>] # set the project default model
penguin config model vision --model-id <upstream_id> --provider <group> [--root <dir>] # set the project vision model (reads images for text-only sessions)
penguin config model list [--root <dir>] # the groups' connections, then the models with the connection each uses; api_key masked, (provider) = from the group, (env) = from an environment variable
penguin config model remove --model-id <upstream_id> --provider <group> [--root <dir>] # remove one modelA group holds one connection — API key, base URL, protocol — in its [providers.<group>] table, and every model in it without a value of its own follows it. Each field resolves on its own from the config file alone: the model's value, else the group's, else nothing (the client's default endpoint, MMSP routing by model id, the environment key where allowed). The built-in catalog is only a reference: a new Project's file already stores each gateway's endpoint and protocol on its group. Set a key once on the group rather than on every model. model add and model remove without --model-id act on the group:
penguin config model add --provider <group> [--api-key <key> | --clear-api-key] [--base-url <url> | --clear-base-url] \
[--client-type <type> | --clear-client-type] [--project-id <id>] [--root <dir>]
penguin config model remove --provider <group> [--project-id <id>] [--root <dir>] # removes the group's connection only; its models stay--clear-* flag.--context-window, --max-tokens, --vision, --fast-mode, --price-*, --set-default) are refused without --model-id; nothing is written.penguin-go and opencode-go included: a model's own protocol always wins over its group's.model add --api-key; the command says how many models keep their own. It reaches only the models that go to the group's endpoint: a model whose own --base-url is on another host (scheme, host and port) needs its own --api-key.--provider and --model-id: the models store nothing and follow the group. Removing the group's last model removes its connection too.The vault holds an agent's environment-variable secrets (third-party API keys etc.); values are injected into that agent's shell subprocesses:
penguin config vault set --key <NAME> --value <value> [--project-id <id>] [--agent-id <id>] [--root <dir>]
penguin config vault list [--project-id <id>] [--agent-id <id>] [--root <dir>] # values are shown masked
penguin config vault remove --key <NAME> [--project-id <id>] [--agent-id <id>] [--root <dir>]--project-id defaults to default_project, --agent-id to default_agent.penguin config lang <en|zh> # persist the CLI language via PENGUIN_LANG in your shell rcpenguin run -m "<task>" [--provider <group> --model-id <id>] [--agent-id <id>] [--workspace <path>] [--approve <mode>] runs one task; penguin chat [--resume [session_id]] starts or resumes an interactive chat with the same options. The model reference stays a pair here too: pass --provider and --model-id together, or neither to run on the project's default model — one without the other is rejected.
Paths use <app_data_dir>, the App Data Dir value from your Environment section.
<app_data_dir>/.project_config.toml — the project's single hidden config file: model list, settings, each group's connection ([providers.<group>]) and the values a model overrides (api_key etc. on its entry). Configuration is CLI-only — never read, print or hand-edit this file.<app_data_dir>/agents/<agent_id>/agent_state/.vault.toml — that agent's vault entries, hidden file; same rule, manage it with penguin config vault.© Prism-Shadow, 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 plugins/agent-development/skills/penguin-config of Prism-Shadow/penguin-harness.
Open the folder on GitHubat commit d56d9ce
Penguin Config 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 |
|---|---|---|---|---|---|---|
| Penguin Config this skillPrism-Shadow/penguin-harness | 2.5k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 | |
| Env Var Conventionssgl-project/sglang | 37k | 2 repos | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Mac Fleet Maintenancesteipete/agent-scripts | 7.3k | — | ~4.8k | Automated safety check: Pass | MIT | |
| Add Config Env Varbaserow/baserow | 6.1k | — | ~1.1k | Automated safety check: Pass | Custom licence |
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
langbot-app/LangBot
Deploys and configures a LangBot instance with Docker Compose or Kubernetes, covering config.yaml, the Box sandbox runtime, the plugin runtime and the global API key.
sgl-project/sglang
Conventions for SGLang environment variables — where to define, how to access, how to name, and how to deprecate.
steipete/agent-scripts
Inventories and maintains a fleet of Macs from a desired-state file: package updates, repo and Xcode sync, and disk, backup and security health reports.
baserow/baserow
Add a Baserow configuration environment variable for the backend, frontend, or both, and propagate it through settings, Nuxt runtime config, Docker Compose, documentation, consumers, and tests as…
TencentEdgeOne/edgeone-makers-tools
EdgeOne Makers CLI command reference. An agent skill from TencentEdgeOne/edgeone-makers-tools.
Prism-Shadow/penguin-harness
Make a reply easier to read and act on with rich blocks inside ordinary Markdown — a choice the user picks from, a form that collects several answers, a procedure as steps with warnings in place, a…
Prism-Shadow/penguin-harness
A skill your agent uses when developing PenguinHarness itself — changing packages/{core,server,web,cli,desktop,landing,docs,skills}, the built-in model catalog, the installers or the release…
Prism-Shadow/penguin-harness
Create and edit Bento presentations — self-contained .bento.html decks whose document is JSON.
Prism-Shadow/penguin-harness
A skill your agent uses when standing PenguinHarness up to try a change by hand — launching the Web App, the desktop shell, the landing page, the docs site or the component gallery to click through…
Prism-Shadow/penguin-harness
A skill your agent uses when changing the PenguinHarness Web App (packages/web) or the shared UI package — adding or restyling any UI, picking a status colour, adding an icon, laying out a row or a…
Prism-Shadow/penguin-harness
Drive the PenguinHarness agent browser — the desktop app's built-in browser or the user's own Chrome — from the shell with penguin browser: open pages, read them as simplified HTML or text, act with…
Categories
Manage model API keys, default models and per-agent vault secrets with the penguin CLI. Penguin Config is an agent skill from Prism-Shadow/penguin-harness. Manage model API keys, default models and per-agent vault secrets with the penguin CLI.
Penguin Config fits situations like: tasks that involve Secrets management.
Run `npx skills add Prism-Shadow/penguin-harness --skill penguin-config -a claude-code`. Or copy the skill folder (plugins/agent-development/skills/penguin-config in Prism-Shadow/penguin-harness) into .claude/skills/penguin-config in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Prism-Shadow/penguin-harness --skill penguin-config -a codex`. Or copy the skill folder (plugins/agent-development/skills/penguin-config in Prism-Shadow/penguin-harness) into .agents/skills/penguin-config 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 Prism-Shadow/penguin-harness --skill penguin-config -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/penguin-config, .gemini/skills/penguin-config, .github/skills/penguin-config and .opencode/skills/penguin-config in your project.
SKILL.md names no scripts, command-line tools or credentials: Penguin Config is instructions for the agent only.
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.
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.
Penguin Config 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 2.3k tokens (SKILL.md is roughly 9.3k 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 Penguin Config: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), LangBot Deployment Guide (langbot-app/LangBot, 18k stars), Env Var Conventions (sgl-project/sglang, 37k stars) and Mac Fleet Maintenance (steipete/agent-scripts, 7.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Prism-Shadow (a GitHub organization) maintains it in Prism-Shadow/penguin-harness, which has 2,464 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on October 7, 2026.
Source: Prism-Shadow/penguin-harness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.