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 pproenca/dot-skills --skill mlflow-mlops-migrationgit clone --depth 1 https://github.com/pproenca/dot-skillsWrote 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/pproenca/dot-skills/mlflow-mlops-migration)<a href="https://agentmods.dev/skills/pproenca/dot-skills/mlflow-mlops-migration"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/mlflow-mlops-migration/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/pproenca/dot-skills/mlflow-mlops-migration"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/mlflow-mlops-migration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00198 | $0.01864 |
| Opus 5 | $0.00099 | $0.00932 |
| Sonnet 5 | $0.00040 | $0.00373 |
| Haiku 4.5 | $0.00020 | $0.00186 |
Grade A, and why
mlflow-mlops-migration 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 5d 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.
- **bash, curl, jq** — the scripts use them How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MLflow MLOps Migration
A phased, gated workflow that turns an arbitrary ML codebase — however unstructured — into a
production-grade open-source MLflow 3 setup covering the full MLOps cycle: tracked experiments,
a domain-modelled registry, dev/staging/prod separation, evaluation-gated promotion, and served
models. It is written to be driven with a developer who has no MLflow 3 experience: every phase
produces a reviewable artifact before anything is changed, and every API decision defers to the
sibling mlflow-3 rule pack (which is pinned to mlflow 3.15.1 and names the
MLflow 2-era idioms this migration exists to remove).
When to Apply
Use this skill when:
- A team wants MLflow (or has a messy/partial MLflow 2 setup) and needs the path to a production-grade MLflow 3 deployment — not just API fixes.
- Training code exists but experiments are untracked, models are shipped by copying files, or "deployment" means a pickle in a bucket.
- You are asked to design or review a dev/staging/prod model-promotion story.
- An MLflow 2 → 3 migration touches infrastructure (stages,
./mlrunsfile stores, MLServer), not only client code.
Don't use it for a single API question — read the relevant mlflow-3 rule directly.
Workflow Overview
0 assess ─▶ 1 domain-model ─▶ 2 environments ─▶ 3 instrument ─▶ 4 promote ─▶ 5 serve ─▶ 6 operate
audit registry tracking per training code eval-gated validate, retrain loop,
report naming, alias env (dev local, → MLflow 3 copy_model_ serve, challenger,
(script, + gate design stg/prod DB+S3 idioms (rule version + smoke-test maintenance
read-only) (interview) + auth) pack) alias flip /invocations (gated)
| Phase | Action | Deliverable | Risk |
|---|---|---|---|
| 0 | Run scripts/00-assess.sh <codebase> — read-only audit |
mlflow-assessment.md report |
read-only |
| 1 | Interview + domain modelling | Registry domain doc (names, aliases, gates) | read-only |
| 2 | Stand up tracking per environments; dev via scripts/scaffold-dev-tracking.sh |
Reachable tracking server(s), config.json filled |
write |
| 3 | Restructure training code to MLflow 3 idioms (sibling rule pack) | Refactored code, first LoggedModels registered | write |
| 4 | Wire promotion — evaluate gate, tags, copy_model_version, alias flip |
Promotion script/CI job | write |
| 5 | Serve — mlflow.models.predict, then serve/build-docker, smoke /invocations |
Served model per environment | write |
| 6 | Operate — retraining, challenger evaluation, maintenance (see workflow) | Runbook habits, scheduled jobs | write |
| ✓ | Run scripts/verify.sh after phases 2–5 |
Pass/fail assertion report | read-only |
What ships with it
13 files 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.
- config.json 1.1 KB
- gotchas.md 1.6 KB
- hooks/hooks.json 561 B
- metadata.json 1.2 KB
- references/assessment.md 3.3 KB
- references/domain-modelling.md 4.0 KB
- references/environments.md 4.6 KB
- references/promotion.md 4.4 KB
- references/serving.md 3.3 KB
- references/workflow.md 6.0 KB
- scripts/00-assess.sh 5.1 KB runs code
- scripts/scaffold-dev-tracking.sh 2.6 KB runs code
- scripts/verify.sh 5.1 KB runs code
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.
- 5d ago First seen · 110 lines · 198 tokens per session scan A 5641b0195a0b
mlflow-mlops-migration is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 198 tokens to every session and 1,864 once invoked, about $0.0010 per session on Opus 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 2026-09-03.
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