retinue: Self-hosted coordination for AI workers: per-task graphs, device/model timelines, progress receipts

by jklthinking · MCP Server · ★ 110

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

Security audit verdict: SAFE · quality 69/100

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-orchestrationagentsai-agentsautomationclaudecodexfastapifeishukanbanllm

Quick Facts

Stars110
Forks3
LanguagePython
CategoryMCP Server
LicenseAGPL-3.0
Quality Score69/100
Open Issues1
Last Updated2026-10-22
Created2026-08-13
Platformsclaude-code, codex, mcp, python
Est. Tokens~15k

About retinue

RETINUE 众卿 — a self-hosted task board for humans and AI agents Website & offline demo · FAQ · English · 简体中文 RETINUE's Chinese name is 众卿 ("the assembled ministers"). RETINUE is a self-hosted task board and orchestration hub for a mixed team of people and AI agents. It keeps one durable baton per piece of work: a task card with a holder, acceptance checks, and an append-only receipt chain.

Compatible Skills

These tools work well together with retinue for enhanced workflows:

  • better-agent — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)

retinue alternative? Top 6 similar tools

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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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