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.
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.
npx skills add Prism-Shadow/penguin-harness --skill agent-initializationgit clone --depth 1 https://github.com/Prism-Shadow/penguin-harnessWrote 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.
[](https://agentmods.dev/skills/prism-shadow/penguin-harness/agent-initialization)<a href="https://agentmods.dev/skills/prism-shadow/penguin-harness/agent-initialization"><img src="https://agentmods.dev/badge/skills/prism-shadow/penguin-harness/agent-initialization/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.
<a href="https://agentmods.dev/skills/prism-shadow/penguin-harness/agent-initialization"><img src="https://agentmods.dev/badge/skills/prism-shadow/penguin-harness/agent-initialization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Rogue Agent · line 63 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.03551 |
| Opus 5.5 | $0.00032 | $0.01420 |
| Sonnet 5.5 | $0.00016 | $0.00710 |
| Haiku 4.5 | $0.00008 | $0.00355 |
Grade A, and why
agent-initialization scanned grade A 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Import.** Fetch a Skill from a URL, a repository or a local path (`curl`, `git clone`, `unzip`), then place it under `skills/`. A Skill written for another tool usually needs only the frontmatter above. Read everythi How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Initialization
This skill initializes an agent's settings from a user requirement — plain files in the target agent's directory. It is also the reference for giving an agent, yourself included, a new Skill or a new hook: both are directories you write, and the harness picks them up from disk.
Before you start
If the user's message only invokes this skill (e.g. "use agent-initialization skill") without a concrete requirement, ask the user what agent they want and what it should do. But when the requirement is already concrete — even a single sentence like "an expert that answers questions about X" — do not ask follow-up questions: derive the role and rules from that sentence, apply the defaults below, and list your assumptions in the final reply.
An Agent Workbench inside PenguinHarness already has its runtime: create the new Agent and follow penguin-plugin for its tab. No SDK/API question is needed. Only an external program without a chosen architecture needs the question below.
An agent for a program
An external program — an app, a service, a bot, a script outside PenguinHarness — reaches a Penguin agent either embedded with the SDK or through the Penguin server's Agent API, and the two put the agent in different places. That choice is the penguin-sdk skill's, in this same plugin: whenever the requested agent is for a program, follow its Ask which way first before you create anything. An agent that people talk to, in the Web App, the CLI or a Remote-control bot, is not for a program and needs no question. Then:
- SDK: no Agent is created in this Project. Build the program with the penguin-sdk skill, and apply this skill to the program's embedded agent (see The embedded agent of an SDK app).
- API: create or configure the Agent here with the rest of this skill. Its API access and keys are the owner's to turn on, never yours; the penguin-sdk skill's The API path and its
reference/agent-api.mdhave the rules and the steps to hand the user.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago Changed · +1 lines · +5 tokens per session f8d228e3cf2c
- 6d ago Changed · -35 lines · -7 tokens per session 15fb4328f71a
- 8d ago Changed · +1 lines 1e0affa8c94d
- 9d ago Changed · +44 lines · +29 tokens per session 7664d06084ea
- 16d ago Changed 7b9c93c1aaee
- 18d ago Changed · +69 lines · +22 tokens per session ecce0b84ba03
- 1mo ago Changed · -4 lines 41a0bc5663e5
- 1mo ago First seen · 108 lines · 30 tokens per session scan A 763d92ed2f4b
agent-initialization is a skill published in the GitHub repository Prism-Shadow/penguin-harness (2,827 stars, last pushed today), licensed Apache-2.0. It adds 79 tokens to every session and 3,551 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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computer-history
Answer questions about what the user recently did on their computer — who contacted them, what they were working on, where they left off — by reading the local Computer History summaries and raw event streams.
dashboard
Update the agent's Control Center. Use when the user says "update my Control Center", "update my dashboard", "redesign my home", or "/dashboard".
co-google
Route Google account work to Gmail, Drive, Calendar, and YouTube CLI commands using one locally saved login.
co-slack
Read and answer Slack with co slack — what a channel said, a thread, a search across the workspace, and a reply in the right thread. Use for "what did.
automation
Instructions for managing scheduled tasks through the host's structured automation tool, including reminders, delayed work, recurring checks, and result delivery.