deep-seek: LLM powered retrieval engine designed to process a ton of sources to collect a comprehensive list of entities

by dzhng · Agent Tool · ★ 518

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentagenticaianthropicdata-retrievalknowledge-graphllmopenairesearch-agesearch

Quick Facts

Stars518
Forks53
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score70/100
Open Issues4
Last Updated2024-05-07
Created2024-03-16
Platformsnode
Est. Tokens~79k

About deep-seek

DeepSeek This is a new experimental architecture for a llm powered internet scale retrieval engine. This architecture is very different from current research agents, which are designed as answer engines.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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