model-onboarding

model-onboarding is a skill for Claude Code from rlaope/oh-my-hermes. It costs 107 tokens per session (1,028 once invoked), scanned A, original, MIT.

A procedure for adding a new language model generation to an AI coding system, including recognition, routing, pricing, configuration, and benchmarking.

In plain words
What is it for?
It helps onboard model aliases, calibrate model traits, update routing tables, set documented prices, and verify served model paths.
Why use it?
It prevents a model from being only partly added by checking its identity, documented behavior, routing paths, and machine configuration together.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions AGENTS.md; mentions Codex.

Good fit It helps onboard model aliases, calibrate model traits, update routing tables, set documented prices, and verify served model paths.

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Install with agentmods
npx agentmods add skills/rlaope/oh-my-hermes/model-onboarding
About the project

oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.

rlaope/oh-my-hermes · 4,206 stars · on GitHub · rlaope.github.io

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 rlaope/oh-my-hermes --skill model-onboarding
Clone the repo
git clone --depth 1 https://github.com/rlaope/oh-my-hermes

Made for: Claude Code.

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 model-onboarding

README.md
[![agentmods](https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/model-onboarding/github.svg)](https://agentmods.dev/skills/rlaope/oh-my-hermes/model-onboarding)
Your own site
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/model-onboarding"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/model-onboarding/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 model-onboarding

Your own site · 80×15
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/model-onboarding"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/model-onboarding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,028 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
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 $0.00107 $0.01028
Opus 5.5 $0.00043 $0.00411
Sonnet 5.5 $0.00021 $0.00206
Haiku 4.5 $0.00011 $0.00103

Measured today against content hash d8216ea3716d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

model-onboarding scanned grade A with 0 findings 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 today.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/model-onboarding/SKILL.md · 77 lines

What it actually says

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:

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, the public docs and site pages, and the pinned-chain tests all name the old id (the "Files that move together" table in the procedure lists them). docs/INSTALLATION.md's chain table is generated (docs chain-table); the two site pages are edited by hand; the READMEs carry no table. git grep the old id across the whole tree and move every site in the same commit. Superseded generations leave the shipped chains 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.

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

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. today Changed · +2 lines d8216ea3716d
  2. 1mo ago Changed · +18 lines 19d85703fc19
  3. 1mo ago Changed · +10 lines 43ef6be29151
  4. 1mo ago First seen · 47 lines · 107 tokens per session scan A 29415a32faea

Subscribe to this mod's changes

model-onboarding is a skill published in the GitHub repository rlaope/oh-my-hermes (4,206 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 1,028 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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