linkly-ai-skills: Agent Skills for Linkly AI — search, browse, and read your local documents from any AI coding agent

by LinklyAI · MCP Server · ★ 67

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

How to install linkly-ai-skills

npx skills add LinklyAI/linkly-ai-skills
npx skills add LinklyAI/linkly-ai-skills -a claude-code

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 74/100

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.

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.

agent-toolsai-searchknowledge-baselocal-firstmcpmemory-managementresearch-toolskills

Quick Facts

Stars67
Forks3
LanguageShell
CategoryMCP Server
LicenseApache-2.0
Quality Score74/100
Open Issues1
Last Updated2026-11-03
Created2026-03-03
Platformscli, mcp
Est. Tokens~12k

About linkly-ai-skills

Linkly AI Skills Agent Skills for Linkly AI — search, browse, and read your local documents (and linked cloud libraries) from any AI coding agent. This skill teaches AI agents how to use Linkly AI's document search capabilities, enabling them to find and read your locally indexed documents (PDF, Markdown, DOCX, PPTX, TXT, HTML, and more) as well as cloud libraries you've linked via Linkly Web.

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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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