Skill rankings

Best customer support skills for AI agents

Find skills for ticket triage, support summarization, knowledge lookup, CRM updates, and response drafting.

Shown: 6 · Candidates: 471

Compare top 4
  1. 01

    DocsGPT

    Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

    @arc53Rag Knowledge18,262
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    85/100
    Quality
    100/100
    Freshness
    47/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    20/100
  2. 02

    Implement

    Implement work from an approved spec or ticket set, run focused and full tests, invoke code review, and commit the result to the current branch.

    @mattpocockCoding175,741
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    100/100
    Quality
    100/100
    Freshness
    0/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    19/100
  3. 03

    Graphify

    A tool that converts codebases, SQL schemas, and other files into queryable knowledge graphs for AI coding assistants.

    @Graphify-LabsDevelopment91,978
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    99/100
    Quality
    100/100
    Freshness
    0/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    19/100
  4. 04

    Understand Anything

    Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

    @Egonex-AIRag Knowledge75,065
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    98/100
    Quality
    100/100
    Freshness
    0/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    19/100
  5. 05

    Cognee

    Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

    @topoteretesRag Knowledge30,192
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    90/100
    Quality
    100/100
    Freshness
    2/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    18/100
  6. 06

    Reverse Skill

    Reverse Engineering / Authorized Penetration Testing / Security Research Skill Router Pack AI-powered routing + On-demand toolchain bootstrapping + Self-evolving knowledge base Supports Claude Code, Kiro, Cursor, Cline, and other AI coding clients 逆向/渗透/安全技能路由包 - AI 自动路由 + 按需自举工具链 + 自动进化经验库 | 支持 Claude Code / Kiro / Cursor / Cline 等代码 AI 客户端

    @zhaoxuya520Development25,600
    Review before use
    Ranking signals

    Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.

    Popularity
    88/100
    Quality
    100/100
    Freshness
    0/100
    Agent evidence
    0/100
    Evidence confidence
    0/100
    Install readiness
    100/100
    Task fit
    18/100

A shortlist from up to 480 directory candidates, not the entire registry. Stars belong to repositories. Signals are not safety guarantees or runtime verification.

How this list works

Matches task and source metadata, then considers quality, popularity and freshness. Source descriptions are not execution evidence.

Signals use a 0–100 scale. They explain the shortlist; the ordering follows this list’s method, not any one score.