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/omh-model-optimization

[omh] Onboarding a newly released model generation: when a model family ships a new generation or changes its serving contract, walk the recognition, research, calibration, routing, and measurement process that keeps model handling honest and current. Use when the user says:

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oh-my-hermes
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$ npx -y skills add rlaope/oh-my-hermes --skill omh-model-optimization --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/omh-model-optimization

Context preview

The summary Claude sees to decide when to auto-load this skill.

[omh] Onboarding a newly released model generation: when a model family ships a new generation or changes its serving contract, walk the recognition, research, calibration, routing, and measurement process that keeps model handling honest and current. Use when the user says:

SKILL.md

omh-model-optimization.SKILL.md
name: "omh-model-optimization"
description: "[omh] Onboarding a newly released model generation: when a model family ships a new generation or changes its serving contract, walk the recognition, research, calibration, routing, and measurement process that keeps model handling honest and current. Use when the user says: model-optimization, model optimization, optimize for model, onboard new model, calibrate new model, new model calibration, model calibration."
metadata:
  hermes:
    tags: [workflow, oh-my-hermes, optimization]
    category: optimization
    phase: model-onboarding
    role: tracker
    quality_tier: evidence-gated

Model Optimization

This is a Hermes-native `model-optimization` workflow skill.

Why This Exists

`model-optimization` exists so a new model release triggers one repeatable, evidence-ordered process instead of ad-hoc edits: recognition proves what the router sees, official-first research separates contracts from folklore, trait-to-counter keeps calibrations concrete, and the measurement close keeps them honest.

Do Not Use When

  • The user wants their own machine's model routing configured or providers connected; use `model-setup`.
  • The goal is measurable performance of an application or system, not model handling; use `ultraperf`.
  • The user wants benchmark-superiority or provider-readiness claims without measurements.

Examples

Good example:

  • Prompt: GLM 5.3 and 5.3 Flash just shipped; check what we should optimize for them.
  • Expected behavior: Probe recognition for both ids, verify family coverage, research the official thinking/tool contract plus community harness handling with labeled sources, draft version-aware trait-to-counter calibration, propose chain placement distinguishing the Flash sibling from the highspeed tier, and name the benchmark pair as the measurement close.
  • Why: A new generation of a known family needs the whole process, not just a chain edit.

Bad example:

  • Prompt: Just say the new model is the best and route everything to it.
  • Expected behavior: Refuse the superiority claim, run the process, and place routing only with owner-approved config or repo changes backed by labeled sources.
  • Why: Unmeasured superiority claims and blanket rerouting are exactly what the process exists to prevent.

Completion Checklist

  • Recognition probe output exists for every new id, and the family label is the expected one.
  • Every research finding is labeled official, official-client, observed, or community with its source kept.
  • The calibration draft counters named traits and marks version-specific rules as such.
  • Routing and pricing changes name their surface (operator config vs repo change) and their approval state.
  • The measurement plan names the benchmark pair, or the recorded reason none can run, and the worse-measured-calibration rule is stated.

Recovery Notes

  • If official docs and community reports conflict, ship the official contract and record the community finding as an unconfirmed counter-signal.
  • If the model cannot be measured (no served route, no credentials), ship the calibration with its research provenance and record the measurement as the named follow-up.
  • If a later measurement shows the calibration worse than baseline, revise or remove it in the same change that reports the number.

Workflow Lane

  • Current lane: **Research and company ops** (`product-docs`, `source-finder`, `web-research`, `research`, `model-optimization`, `inference-serving`, `model-finetuning`, `research-brief`, `+20 more`) - research, signals, ops, and briefings.
  • If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow.
  • Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.

Use When

Use when a model or family is new to OMH, shipped a new generation, or changed its serving contract, and the operator wants recognition, calibration, routing, pricing, and docs checked and strengthened for it through the fixed onboarding process.

Strong routing signals: `model-optimization`, `model optimization`, `optimize for model`, `onboard new model`, `calibrate new model`, `new model calibration`, `model calibration`

Catalog Metadata

Category: `optimization` Phase: `model-onboarding` Hermes role: `tracker` Quality tier: `evidence-gated` Reasoning demand: `heavy`

Quality bar:

  • Probe recognition before researching: `omh coding model-route --executor hermes --model <id> --effort <effort> --role implementation --json` shows the family label the routing engine assigns; an unknown or generic label means the family prefix table needs a row before any calibration can attach.
  • Check calibration coverage second: the MODEL_OPTI.md coverage matrix plus both calibration tables (subagent high-effort and composer). A recognized family with no calibration is a tracked gap, not an error.
  • Research official docs first — release notes, thinking/tool-calling contract, context and output limits, pricing, speed tiers — then how other open-source harnesses handle the model. Label every finding official, official-client (the vendor's own client source), observed, or community and keep the source; on conflict the earlier label wins.
  • Author calibration as trait-to-counter: name the model's documented or observed behavior, then state the concrete counter-behavior, version-aware where generations differ. Do not restate universal protocol rules inside a family entry.
  • Distinguish speed tiers from separate models before touching routing: a speed tier is the same weights served faster and projects onto its base model; a separately trained sibling is its own chain entry. Place routing through config surfaces first (omh model-chains set, omh coding category-maestro set); shipped editorial defaults change only as a repo change with explicit owner approval; a superseded generation leaves the shipped chains, and its retired alias stays recognized and priced
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