penguin-config

penguin-config is a skill for Claude Code, Codex from Prism-Shadow/penguin-harness. It costs 22 tokens per session (1,368 once invoked), scanned B, original, Apache-2.0.

A command-line guide for configuring model providers, model names, API keys, defaults, and per-agent secret storage with the penguin tool. A command-line tool is a program operated by typing commands in a terminal.

In plain words
What is it for?
Use it to add or update model connections, list configured models, choose a default, and manage agent-specific vault secrets.
Why use it?
It keeps model configuration in the supported CLI instead of requiring users to find and edit hidden files directly.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to add or update model connections, list configured models, choose a default, and manage agent-specific vault secrets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/prism-shadow/penguin-harness/penguin-config
About the project

PenguinHarness is a local-first platform in which multiple AI agents create, evaluate, optimize, and deploy agent applications. It is for people building AI software who want agents to generate applications and improve their own behavior through skills.

Prism-Shadow/penguin-harness · 2,048 stars · on GitHub · penguin.ooo

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Prism-Shadow/penguin-harness --skill penguin-config
Clone the repo
git clone --depth 1 https://github.com/Prism-Shadow/penguin-harness

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for penguin-config

README.md
[![agentmods](https://agentmods.dev/badge/skills/prism-shadow/penguin-harness/penguin-config/github.svg)](https://agentmods.dev/skills/prism-shadow/penguin-harness/penguin-config)
Your own site
<a href="https://agentmods.dev/skills/prism-shadow/penguin-harness/penguin-config"><img src="https://agentmods.dev/badge/skills/prism-shadow/penguin-harness/penguin-config/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for penguin-config

Your own site · 80×15
<a href="https://agentmods.dev/skills/prism-shadow/penguin-harness/penguin-config"><img src="https://agentmods.dev/badge/skills/prism-shadow/penguin-harness/penguin-config.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,368 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 12
    Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.
    Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
  • medium Rogue Agent · line 21
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.01368
Opus 5 $0.00011 $0.00684
Sonnet 5 $0.00004 $0.00274
Haiku 4.5 $0.00002 $0.00137

Measured 5d ago against content hash 52199f3c9e8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade B, and why

penguin-config scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Unrestricted tool accessmediumExcessive agency

A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.

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.
plugins/agent-development/skills/penguin-config/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Penguin Config (CLI)

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 and penguin config model list shows the models currently available. Configuration goes through the CLI only — never read or hand-edit the underlying hidden files.

Before you start

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.

Models

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>] [--base-url <url>] \
  [--client-type <type>] [--context-window <n>] [--max-tokens <n>] [--vision | --no-vision] \
  [--price-cache-read <n>] [--price-cache-write <n>] [--price-output <n>] \
  [--project-id <id>] [--root <dir>] [--set-default]
  • A model is identified by the (provider, model_id) pair, so --provider and --model-id are both required — 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).
  • For any OpenAI chat-completion compatible endpoint use --client-type openai --base-url <endpoint>; omit --client-type to auto-route by model id.
  • Prices are USD per million tokens (cache read / cache write / output).
  • --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.
  • All 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:
    • Penguin's own model (self-configuration: the model Penguin itself runs on): the default root without --root is correct.
    • An AI app you are building: --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.
    • While developing an app, review regularly: penguin config model list --root <app root> should show the app's entries, and the global list (no --root) should stay clean.

Read the full file on GitHub · 72 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 72 lines · 22 tokens per session scan B 52199f3c9e8f

Subscribe to this mod's changes

penguin-config is a skill published in the GitHub repository Prism-Shadow/penguin-harness (2,048 stars, last pushed yesterday), licensed Apache-2.0. It adds 22 tokens to every session and 1,368 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

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