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Agent skill

Model Onboarding

by rlaope in rlaope/oh-my-hermes

Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from…

MITAuto-check: notesBusiness, Finance & HR

Install Model Onboarding

skills CLI
$ npx skills add rlaope/oh-my-hermes --skill model-onboarding -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rlaope/oh-my-hermes model-onboarding --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rlaope/oh-my-hermes.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/model-onboarding .claude/skills/model-onboarding && rm -rf skills-src

Use ~/.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/

Facts

Skill name
model-onboarding
GitHub stars
3.2k
Token cost
~1k tokens
SKILL.md length
506 words
Files
1
Skills in repo
143
Repo updated
First seen
Licence
MIT

At a glance

Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from…

  • A model family ships a new generation (for example Fable 5.1 is out
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • GLM 5.4 shipped
  • Onboard new model

What it does

Model Onboarding is an agent skill from rlaope/oh-my-hermes. Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from documented list only, gate machine config on a served route, prove with the gates, close with a benchmark pair. Use when a model family ships a new generation (for example "Fable 5.1 is out", "GLM 5.4 shipped", "onboard new model", "add model to chains").

Its SKILL.md is about 1k 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 Business, Finance & HR, covering Performance reviews. It works with Zhipu GLM and DeepSeek. The repository describes itself as: All in one plugin for Hermes Agent ⚚ the coding intelligence, a long-term memory system and model optimized workflow packages. The licence is MIT.

When your agent uses it

  • A model family ships a new generation (for example Fable 5.1 is out
  • GLM 5.4 shipped
  • Onboard new model
  • Add model to chains)

Example prompts

  • “Fable 5.1 is out”
  • “GLM 5.4 shipped”
  • “onboard new model”
  • “/model-onboarding”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Read, Grep, Glob, Edit, Write

What it can do on your machine

Read from SKILL.md and the folder at commit f772a94. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Grep
    • Glob
    • Edit
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Model Onboarding loads about 1k tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 506 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Grep, Glob, Edit, Write

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.

SKILL.md

The full file from rlaope/oh-my-hermes at commit f772a94, republished under its MIT licence (© rlaope). 506 words, ~1,006 tokens.

Download SKILL.mdSave it as .claude/skills/model-onboarding/SKILL.md (or your agent's skills folder).
name
model-onboarding
description
Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from documented list only, gate machine config on a served route, prove with the gates, close with a benchmark pair. Use when a model family ships a new generation (for example "Fable 5.1 is out", "GLM 5.4 shipped", "onboard new model", "add model to chains").
allowed-tools
Bash, Read, Grep, Glob, Edit, Write

Model onboarding

The procedure lives in docs/MODEL-ONBOARDING.md. Read that file and follow it in order.

It is kept there rather than here because Codex, Hermes handoffs, and generic executor profiles run the same loop, and AGENTS.md requires that no single executor own a shared surface. This file exists so the loop is reachable as /model-onboarding; it holds no rules of its own.

Start by reading, in this order:

sh
cat docs/MODEL-ONBOARDING.md
cat MODEL_OPTI.md

Nine things the loop gets wrong most often:

  • Recognition before research. Probe every served id and every bare chat name with omh coding model-route first; a model_family of unknown means the calibration never attaches. Probe the dated snapshot form too (<id>-YYYY-MM-DD): some providers serve only that spelling, and it must resolve the base's contract, chain position, price, and HUD label through dated_snapshot_base() rather than falling to generic.
  • The chain names the id the vendor's API serves, not the model card's spelling. Read the Hermes provider profile for the family before choosing the alias — DeepSeek serves deepseek-flash and 400s deepseek-v4.1-flash; the versioned contract sits behind the pointer as a declared projection and in EXACT_CONTRACT_POINTER_ALIASES.
  • Research runs as four parallel read-only lanes (official docs, Hermes runtime source, the vendor's own harness, community harnesses), each a labeled dossier under .omc/research/; the Hermes lane is the one that shows what the wire carries (id folding, effort overrides, passback).
  • Chains move as a set. The Hermes-lane table, its plugin mirror, the Maestro-lane table, the model-setup skill text, seven public doc surfaces, the release budget note, and the pinned-chain tests all name the old id; grep src/ tests/ docs/ README* site/ for it and move every site in the same commit. Superseded generations leave the shipped chains (owner decision, 2026-09-11) and join the recognition-only list; pins hide in fixtures, so start the full suite in the background at the chain edit.
  • Machine config stays provider-neutral. Chains name aliases; the provider row is a separate concern in model-providers.json. Place the id with omh model-chains set, never by hand-editing the JSON; an operator may keep an older generation behind it there, the shipped table does not.
  • Served is not released. Prove the route with one hermes --oneshot call and read the usage file (model, provider, cost_status) before any measurement or placement; gateways want the vendor-prefixed id.
  • The override is measured against the block it replaced, on cost. Run the family arm next to baseline and optimized; expect pass rate to tie and read the paired token delta, tool calls, and turns. Same pass with more tokens on the tasks it fails is a sentence that pushes — cut it.
  • A routing signal is only as good as the tier's chain head. Measure the head on the request class it will receive before shipping the signal, and name the head in every routing claim.
  • A separate reviewer lane reads the diff before the commit. The DeepSeek round's reviewer caught a reverse projection that let -pro / -fast / -flex aliases label their base id; self-review did not.
Show full SKILL.md (13 more words)Show less

Arguments pass through verbatim: the model ids as served (for example claude-fable-5-1 claude-mythos-5-1).

© rlaope, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/model-onboarding of rlaope/oh-my-hermes.

Open the folder on GitHubat commit f772a94

Compare with similar skills

Model Onboarding 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.

Model Onboarding compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Model Onboarding this skillrlaope/oh-my-hermes3.2k—~1kAutomated safety check: NotesMIT
Weave Router Local Testingweave-os/router5.6k—~3.1kAutomated safety check: NotesApache-2.0
AI Model NodejsTencentCloudBase/CloudBase-AI-Toolkit1.1k3 repos~5kAutomated safety check: PassMIT
LLM Council on Fireworks AIdair-ai/dair-academy-plugins614—~5kAutomated safety check: NotesMIT
Quota Axikunchenguid/quota-axi144—~547Automated safety check: PassMIT
Auto Review Loop LLMAI4Scientist/nano-scientist1284 repos~1.8kAutomated safety check: WarnNone

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Works with

Categories

Questions about Model Onboarding

What does Model Onboarding do?

Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from…. Model Onboarding is an agent skill from rlaope/oh-my-hermes. Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from documented list only, gate machine config on a served route, prove with the gates, close with a benchmark pair.

When should I use Model Onboarding?

Model Onboarding fits situations like: A model family ships a new generation (for example Fable 5.1 is out; GLM 5.4 shipped; onboard new model; add model to chains).

How do I install Model Onboarding in Claude Code?

Run `npx skills add rlaope/oh-my-hermes --skill model-onboarding -a claude-code`. Or copy the skill folder (.claude/skills/model-onboarding in rlaope/oh-my-hermes) into .claude/skills/model-onboarding in your project. Claude Code loads it when a task matches its description.

How do I install Model Onboarding in Codex?

Run `npx skills add rlaope/oh-my-hermes --skill model-onboarding -a codex`. Or copy the skill folder (.claude/skills/model-onboarding in rlaope/oh-my-hermes) into .agents/skills/model-onboarding in your project. Codex loads it when a task matches its description.

Can I use Model Onboarding in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rlaope/oh-my-hermes --skill model-onboarding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/model-onboarding, .gemini/skills/model-onboarding, .github/skills/model-onboarding and .opencode/skills/model-onboarding in your project.

What does Model Onboarding need to run?

SKILL.md names no scripts, command-line tools or credentials: Model Onboarding is instructions for the agent only. Its frontmatter pre-approves these tools: Bash, Read, Grep, Glob, Edit, Write.

Does Model Onboarding access the network?

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.

Is Model Onboarding safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Model Onboarding use?

Model Onboarding is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Model Onboarding use?

About 1k tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Model Onboarding?

Skills that share tags, products or a category with Model Onboarding: Weave Router Local Testing (weave-os/router, 5.6k stars), AI Model Nodejs (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars), LLM Council on Fireworks AI (dair-ai/dair-academy-plugins, 614 stars) and Quota Axi (kunchenguid/quota-axi, 144 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Model Onboarding?

rlaope (a GitHub user) maintains it in rlaope/oh-my-hermes, which has 3,207 GitHub stars. The repository holds 143 skills in this directory. The repository was last updated on October 8, 2026.

Source: rlaope/oh-my-hermes on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.