danghuangshang

danghuangshang is an openclaw-based multi-agent collaboration system (AI “court”) that dispatches tasks across role-specific agents (e.g., 内阁/六部/都察院 style) via chat platforms like Discord/Feishu and can also do GitHub code review workflows. It provides scripts for installation, regime switching (ming/tang/modern), memory persistence/backup, a web dashboard, and various integrations/tools.

Evaluated Mar 30, 2026 (0d ago)
Homepage ↗ Repo ↗ Ai Ml ai-ml ai-agents ai-orchestration multi-agent discord-bot self-hosted openclaw workflow-automation github-integration memory-backup web-dashboard
⚙ Agent Friendliness
39
/ 100
Can an agent use this?
🔒 Security
52
/ 100
Is it safe for agents?
⚡ Reliability
32
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
45
Error Messages
0
Auth Simplicity
60
Rate Limits
35

🔒 Security

TLS Enforcement
70
Auth Strength
55
Scope Granularity
30
Dep. Hygiene
50
Secret Handling
55

README references webhook signature verification (security update) and includes explicit Discord multi-bot safety guidance (allowBots="mentions"; avoid @everyone). However, provided data does not describe fine-grained authorization scopes, secure storage mechanisms (vault/HSM) beyond config files, or comprehensive threat-model/error-handling for auth failures.

⚡ Reliability

Uptime/SLA
0
Version Stability
45
Breaking Changes
40
Error Recovery
45
AF Security Reliability

Best When

You want a self-hosted, multi-agent orchestration setup with chat-based triggers (mentions), persistent per-agent memory, and optional GitHub review automation.

Avoid When

You cannot safely run bots/webhooks (webhook signing must be configured; Discord looping must be prevented) or you need a simple single-agent chat API.

Use Cases

  • Multi-agent task delegation and orchestration (e.g., plan → execute → review loops)
  • Discord-based agent collaboration for coding, documentation, and reviews
  • GitHub PR/CI assisted workflows and automated code review
  • Long-running agent memory with backup/restore
  • Running a self-hosted agent “team” with a web dashboard
  • Content generation and structured multi-agent workflows (e.g., Hanlin novel writing template)

Not For

  • A hosted SaaS that requires no self-management (it’s primarily self-hosted)
  • Turnkey enterprise compliance (no explicit compliance/security certifications stated in provided data)
  • Environments where outbound network access to LLM/Discord/Feishu/Notion is prohibited
  • Strictly REST/OpenAPI client integrations without platform-specific event handling

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
No
Webhooks
Yes

Authentication

Methods: Discord bot token (Bot auth) Feishu app credentials (App ID/Secret) for events Notion integration secret (api key / secret) LLM provider API keys (LLM access; per agent/config)
OAuth: No Scopes: No

No OAuth-style delegated scopes are described in provided content. Auth is primarily via platform tokens/secrets configured in openclaw/related config. The README mentions webhook signature validation (for security updates) and Discord safety settings (allowBots).

Pricing

Free tier: No
Requires CC: No

Project is MIT licensed and self-hosted; costs primarily come from LLM usage plus hosting.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Discord multi-bot looping risk: must set allowBots to "mentions" and avoid @everyone to prevent message storms.
  • Remote installation is not described as idempotent; behavior may depend on existing OpenClaw install state.
  • Memory persistence requires backups; losing memory is described as effectively irreversible.

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Scores are editorial opinions as of 2026-03-30.

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