Analytics & Monitoring·v0.0.0-placeholder

Fine-Tuning on Microsoft Foundry Agent Skill

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders).

Context cost
15.6k tokensestimated from the bundle, loaded when it triggers
Bundle
33 files · 188.4 kB15 scripts among them — read before you run
Licence
MITthe author’s own terms
Last change
—v0.0.0-placeholder
Servers it uses
Noneruns standalone

What it does

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

data science

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md5.5 kB · preview
--- name: finetuning license: MIT metadata: author: Microsoft version: "0.0.0-placeholder" ---
10# Fine-Tuning on Microsoft Foundry
11
12Fine-tune models using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset prep, training, deployment, and evaluation.
13
14## When to Use
15
16Use this sub-skill when the user asks about:
17- Fine-tuning a model (SFT, DPO, or RFT)
18- Preparing, validating, or formatting training data
19- Submitting, monitoring, or diagnosing training jobs
20- Calibrating graders or pass thresholds for RFT
21- Deploying or evaluating a fine-tuned model
22- Choosing between training types (SFT vs DPO vs RFT)
23- Distillation, synthetic data generation, or dataset quality scoring
24- Large file uploads for training data
25- Cleaning up fine-tuning resources (files, deployments)
26
27**Do NOT use for:** General model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).
28
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md658 words
Files33
LicenceMIT
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈170
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
15,455
on trigger
The instruction body and 32 supporting files, read only when the skill fires.
7.8%
of a 200k window
Ten skills this size would take about 78% of the window before you open a file.
050k100k150k200k context window

15.6k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

33 files, 188.4 kB on disk. Mostly text — the instructions the model reads — with 15 scripts in it that your client would run only if the instructions tell it to.

  • SKILL.md5.5 kB
  • references/agentic-rft.md3.2 kB
  • references/dataset-formats.md3.7 kB
  • references/deployment.md3.5 kB
  • references/evaluation.md5.9 kB
  • references/grader-design.md3.4 kB
  • references/hyperparameters.md3.2 kB
  • references/large-file-uploads.md0.9 kB
  • references/platform-gotchas.md2.1 kB
  • references/reward-hacking.md2.9 kB
  • references/training-curves.md4.2 kB
  • references/training-types.md3.2 kB
  • references/vision-fine-tuning.md4.2 kB
  • scripts/calibrate_grader.py9.5 kB
  • scripts/check_training.py8.0 kB
  • scripts/cleanup.py9.7 kB
  • scripts/common.py7.8 kB
  • scripts/convert_dataset.py10.9 kB
  • scripts/deploy_model.py9.6 kB
  • scripts/evaluate_model.py11.7 kB
  • scripts/generate_distillation_data.py10.3 kB
  • scripts/monitor_training.py5.9 kB
  • scripts/score_dataset.py7.9 kB
  • scripts/submit_training.py11.1 kB
  • workflows/dataset-creation.md3.2 kB
  • workflows/diagnose-poor-results.md2.4 kB
  • workflows/full-pipeline.md3.2 kB
  • workflows/iterative-training.md3.2 kB
  • workflows/quickstart.md4.6 kB
  • scripts/validate/data_stats.py6.3 kB
  • scripts/validate/validate_dpo.py3.8 kB
  • scripts/validate/validate_rft.py8.8 kB
  • scripts/validate/validate_sft.py4.6 kB
What is not in it

A skill installs nothing and depends on nothing: it is a folder your client reads. This one carries 15 scripts beside the text, so the bundle is 33 files you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Fine-Tuning on Microsoft Foundry · 15.6k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/stark3998-fine-tuning-on-microsoft-foundry/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/fine-tuning-on-microsoft-foundry" ] && { [ ! -e .claude/skills/fine-tuning-on-microsoft-foundry ] || { mv .claude/skills/fine-tuning-on-microsoft-foundry "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/fine-tuning-on-microsoft-foundry" .claude/skills/ && echo "Installed .claude/skills/fine-tuning-on-microsoft-foundry"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add stark3998/fine-tuning-on-microsoft-foundry

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/fine-tuning-on-microsoft-foundry/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/stark3998-fine-tuning-on-microsoft-foundry/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/fine-tuning-on-microsoft-foundry" ] && { [ ! -e ~/.claude/skills/fine-tuning-on-microsoft-foundry ] || { mv ~/.claude/skills/fine-tuning-on-microsoft-foundry "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/fine-tuning-on-microsoft-foundry" ~/.claude/skills/ && echo "Installed ~/.claude/skills/fine-tuning-on-microsoft-foundry" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/fine-tuning-on-microsoft-foundry/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where. It appears as finetuning in Gemini CLI, Codex, Copilot and Grok (its own name); Claude Code lists it by the folder name, fine-tuning-on-microsoft-foundry.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Version0.0.0-placeholder
Publishedno release date on file
PriceFree
Referencestark3998/fine-tuning-on-microsoft-foundry

Versions

v0.0.0-placeholder is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v0.0.0-placeholder
  • No earlier releases have been published to the marketplace.
Pinning

The install command always fetches the release that is current the day you run it — v0.0.0-placeholder today — and cannot ask for an earlier one. The copy on your disk does not change until you run it again.

Reviews

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