Deploy Python Workloads on Modal
Cloud deployment requires correct images, resources, secrets, storage, and scaling settings. This skill guides Claude, Codex, and Claude Code through practical Modal workflows.
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Review the Skillstore skill "modal" from https://skillstore.io/skills/davila7-modal.md and its manifest at https://skillstore.io/api/skills/davila7-modal/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
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Using "modal". Deploy a text classifier on one GPU with low idle cost.
Expected outcome:
A deployment plan using a cost-appropriate GPU, cached model weights, scale-to-zero behavior, bounded concurrency, and a protected inference endpoint.
Using "modal". Process one thousand files every night and preserve summaries.
Expected outcome:
A scheduled batch design with mapped file processing, explicit resource limits, a persistent results volume, retry guidance, and completion monitoring.
Using "modal". Reduce cold starts for a frequently used model API.
Expected outcome:
A tuning proposal covering minimum warm containers, image caching, model initialization, concurrency targets, latency measurement, and cost tradeoffs.
Most alerts are false positives from Markdown, framework method names, placeholders, and expected Modal APIs. Confirmed examples expose credentials, log secrets, serve the container root, and use unpinned source.
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
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https://skillstore.io/skills/davila7-modal/audits/10?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/davila7-modal?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/davila7-modal?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/davila7-modal/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/davila7-modal.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>davila7. (2026). modal security audit report (audit version 10) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-modal/audits/10@techreport{davila7-davila7-modal-2026,
author = {davila7},
title = {modal security audit report (audit version 10)},
institution = {Skillstore},
year = {2026},
number = {10},
url = {https://skillstore.io/skills/davila7-modal/audits/10},
note = {Author version unspecified}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "modal security audit report (audit version 10)"
version: "unspecified"
type: report
authors:
- name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-modal/audits/10"
identifiers:
- type: other
value: "skillstore:davila7-modal:audit:10"
description: "Skillstore immutable audit report identifier"
Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
k-dense-ai-modal
2026-08-21
davila7-modal
2026-08-21
Plan a container image, GPU selection, model loading lifecycle, endpoint, and scaling policy for an inference service.
Design mapped batch functions, scheduled collection jobs, persistent volumes, retries, and resource limits for data processing.
Create repeatable deployment patterns for images, secrets, APIs, concurrency, observability, and cost controls.
Create a minimal Modal function for [task]. List prerequisites, image dependencies, local run steps, and expected output.
Design a Modal GPU workload for [model]. Recommend the GPU, image packages, memory, timeout, caching, and validation steps.
Design a Modal job that runs [schedule], calls [source], stores results in a Volume, and handles secrets, retries, and failures.
Architect a secure Modal inference API for [traffic profile]. Cover authentication, model lifecycle, concurrency, autoscaling, observability, rollback, and cost controls.
Author
davila7License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
c43861a65bb95efcae259cd161c9d6f4dc7eec6f
Maintenance freshness
7/24/2026
Usage
5 downloads · 535 views
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