@AaronKal-ECU/offline-ai-agent

Run AI on your own hardware, never deal with the cloud and create AI that can handle sensitive data. This repo showcases how to run AI on your own computer, and how to build specialised tools for it to use. I showcase a real setup where I developed tools in Deepseek Harness, that solved real automation engineering problems

PluginDeveloperAutomationDataGitHub integration

Verification

L1 · Found

Risk

Pending

Health

Active

Trust

Unrated

Install verification: No L4/L5 install test yetInstall verification details →

What it does

Installation

dsh plugin --profile web add github:AaronKal-ECU/offline-ai-agent

verified

Install method: GitHub · install spec unknown (L3 unknown)

Verification & Compatibility

Grouped by plugin version: each card lists the dsh versions actually tested against that artifact version and their install verdicts (L5 wins). Untested combinations are omitted — absence means untested, never assumed compatible. L1–L3 are a plugin-level static archive (independent of the dsh version — the same verdict on every dsh row): they sit in each row's level grid next to L4/L5, marked "static", while their evidence is stored once per plugin inside that row's "checks & evidence" instead of being duplicated per version.

External credentials (plugin-level): none detected

Declared DSH compatibilityfrom package.json · peerDependencies

package manifest not collected

package manifest not collected — the declared range is unknown.

Install compatibility (by plugin version, dsh versions within)

Legend:✓ L5 runtime verified○ ecosystem plugin◼ ecosystem app✗ failed

6d71balocal2026-10-28

No runtime install test for this version (static scan only) — compatibility unknown, never assumed.

29f128github2026-10-28

https://github.com/AaronKal-ECU/offline-ai-agent

No runtime install test for this version (static scan only) — compatibility unknown, never assumed.

Author badges

Embed the official badges in your README to showcase security & install-test status:

Security Report

Two automated layers, neither a manual review: a static scan (per-plugin rule checks) and a model-driven dynamic security audit that covers only the subset static-flagged at warn or above and never executes plugin code.

offline-ai-agentAutomated review · daily

Static n/a; dynamic no conclusion (static stands) → overall low.

no static verdict→dynamic no conclusion→overall low

static findings0 critical·0 high·— files scanned

lowoverall · low

1static scandeterministic rules · no code execution · shape only

Version binding

plugin version—

scanned version—

current version052f4feab2c6

The scan result is valid for the scanned commit. New commits within 7 days are tolerated (the rating still counts); after 7 days without a rescan the badge shows outdated.

2dynamic auditmodel reads redacted source context · never executes plugin code

not in the dynamic queue (the queue only covers plugins whose static tier is medium or above — medium/high/critical; since 2026-10-24 entries rated low are not audited even when dsh-only rules logged warnings) — this does not mean the dynamic audit found it safe.

Rule (2026-10-28): when a dynamic conclusion exists it is authoritative (it may raise or lower the level); the static scan tier (vet primary, dsh backstop) applies only when there is none (not queued / audit failed / withdrawn). The audit never writes the exemption list (exemptions are manual only); a wrong conclusion is withdrawn by human review and the tier falls back to the static scan tier.

Disclaimer: the static scan and the dynamic security audit are both automated analysis, not a security guarantee. Always review what you install.

Activity

Last commit 2026-10-27 · activity: Active

• Repo created: 2026-10-26

• Stars: ★ 3 · Forks: 0

• Health: Active — committed within last 30 days

Source

GitHub: github.com/AaronKal-ECU/offline-ai-agent

Plugin notes

What is the @AaronKal-ECU/offline-ai-agent DeepSeek Harness plugin?

@AaronKal-ECU/offline-ai-agent is a DeepSeek Harness plugin maintained by @AaronKal-ECU. It is cataloged on dsh.so as a Developer plugin for GitHub integration tasks, with a public GitHub source, declared install command, and automated static scan results; plugins static-flagged at warn or above also carry a model-driven dynamic security audit record.

How do I install @AaronKal-ECU/offline-ai-agent?

Run dsh plugin --profile web add github:AaronKal-ECU/offline-ai-agent in a DeepSeek Harness (dsh) environment. The command is parsed from the plugin manifest, but its install spec is not yet verified (L3); sandbox install and runtime testing have not passed.

How does the security scan relate to a manual audit?

Both layers are automated, not a manual audit: the static scan is heuristic analysis of the repository source (it can produce false positives and miss context), and the dynamic security audit has a model read the harvested source context with secret files stripped and content redacted inline — plugin code is never executed. The dynamic audit only covers plugins static-flagged at warn or above; when it reaches a conclusion that conclusion is authoritative for the combined verdict — it may raise or lower it — and the static scan verdict (vet primary, dsh backstop) applies only when there is none. Exemptions stay manual: the audit never writes the suppression list. Neither layer is a manual security audit or an endorsement; before using a plugin, review the repository and installed permissions, and combine both with the verification level (L4/L5) and health signals.

"DeepSeek Harness (dsh) is an open-source agent harness developed by DeepSeek AI. It uses an architecture where everything is a plugin, and is powered by Cordis."
— DeepSeek Harness README

Sources: GitHub repository · DeepSeek Harness README · security scan data · Maintained by dsh.so · Last updated 2026-10-28