Plan Bounded Deep Learning Experiments
Exploratory training can consume budgets without producing comparable evidence. This skill ranks limited variants and records results for careful human review.
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Review the Skillstore skill "explore-run" from https://skillstore.io/skills/lllllllama-explore-run.md and its manifest at https://skillstore.io/api/skills/lllllllama-explore-run/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "explore-run". Plan learning-rate probes on a ten-percent subset with three short runs.
Expected outcome:
A ranked list of three bounded variants, estimated costs, selection reasons, and baseline isolation requirements.
Using "explore-run". Compare completed runs using validation loss as the minimized metric.
Expected outcome:
Using "explore-run". Reduce a large variant grid to four affordable candidates.
Expected outcome:
Four budget-compliant candidates ranked by the configured cost, success, and gain weights.
All 21 static findings are false positives caused by Markdown code spans, documentation links, or restrictive policy text. No malicious intent, prompt injection, command execution, or unsafe filesystem operation was found.
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https://skillstore.io/skills/lllllllama-explore-run/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/lllllllama-explore-run?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/lllllllama-explore-run?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/lllllllama-explore-run/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/lllllllama-explore-run.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>lllllllama. (2026). explore-run security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/lllllllama-explore-run/audits/7@techreport{lllllllama-lllllllama-explore-run-2026,
author = {lllllllama},
title = {explore-run security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/lllllllama-explore-run/audits/7},
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: "explore-run security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "lllllllama"
date-released: "2026-08-08"
url: "https://skillstore.io/skills/lllllllama-explore-run/audits/7"
identifiers:
- type: other
value: "skillstore:lllllllama-explore-run:audit:7"
description: "Skillstore immutable audit report identifier"
Create a small candidate matrix before committing resources to full training.
Rank bounded experiments by estimated cost, success probability, and expected gain.
Document comparability limits and top candidates before approving further validation.
Plan a small-subset probe for [research goal]. Use [subset size] and [step limit]. Keep the trusted baseline unchanged.
Build variants for [parameter axes]. Limit the plan to [maximum variants] and [maximum short-cycle runs]. Rank candidates conservatively.
Rank candidates using these weights: cost [value], success rate [value], and expected gain [value]. Explain the highest-ranked choices.
Review results for [primary metric] with a [maximize or minimize] goal. Separate measured evidence from heuristic predictions and note unfair comparisons.
Author
lllllllamaLicense
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Ref
656be3040aef5c047555a908cd5c695d22a4a548
Maintenance freshness
8/8/2026
Usage
7 downloads · 1 views
File structure
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