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Editorial collection · updated 2026-09-16

Best DSH agent and automation plugins

Six DeepSeek Harness plugins for orchestration, evaluation gates and long-running autonomous work that stays reviewable.

This collection selects 6 plugins from the directory. Their verification levels are L1 1, L2 2, L3 3, L4 0, L5 0: L3 means the install command was parsed and a compatibility target declared, while L1 means only the repository and its README were confirmed. No pick has been installed or run in a sandbox, so none claims L4 or L5. 0 of 6 have passed an automated security scan, and the other 6 are marked unverified rather than safe. Declared compatibility targets are unstated 3, 0.1.5-rc.1 || 0.1.2-rc.1 1, >=0.1.2-rc.1 <0.2.0 || >=0.1.5-alpha.1 <0.2.0 1, 0.1.2-rc.1 || 0.1.5-rc.2 1. Together the picks carry 12,561 GitHub stars, and the most recently checked is Aegis (2026-09-18). Every listing below records its own licence, language and last-checked date, so a claim here can be traced back to the listing it came from. Selection weighed capability gain and maintenance through the preview churn rather than star count, so read the list below as a build order rather than a ranking.

Written by Chiyu · Maintainer and editor

Maintains this directory: checks every install command against the published package, assigns verification levels, runs the automated scans, and writes the guides. ·

Plugins in this collection

Editor's pick

A spec-first agent OS for AI coding — Socratic interview, immutable Seed, staged evaluation, MCP server.

L2
6k Python

Aegis

GanyuanRan

A method pack that makes agents plan against your project baseline, prove completion with fresh evidence, and leave simple tasks on the fast path.

L2
1.2k Python

Agent Teams

NanmiCoder

An AgentTeams orchestration plugin that runs several agents as a coordinated team inside DSH.

L3
1.7k JavaScript

Auto Review

PerryLink

Puts a second model on the approval chain — a read-only reviewer subagent returns a structured allow/deny verdict, and a reviewer failure denies instead of allowing.

L3
181 TypeScript

OpenBiliClaw

whiteguo233

Local-first content discovery agent that learns your interests, then hunts the open web and social platforms for you.

L1
3.3k Python

Memento

PerryLink

Bounded, layered, approval-gated cross-session memory for DeepSeek Harness — a memory service plus a local SQLite store.

L3
102 TypeScript

Agent plugins are the highest-leverage category in the ecosystem and the easiest place to lose control of a session. Each pick here has an explicit mechanism for stopping, checking or reviewing what the agent did.

Ouroboros

The strongest answer to self-graded work: an interview gate before the task starts, staged evaluation during it, and a budgeted loop that stops when the budget is spent rather than when the agent feels finished.

Aegis

Records an architecture baseline, then flags drift from it and requires evidence before a task counts as complete. Best suited to long tasks where the risk is the system quietly changing shape.

Agent Teams

Splits work across named teammates with their own roles, coordinated by a lead agent. Useful when a task is genuinely parallel rather than merely large.

Auto Review

Puts a second model on the approval chain: a read-only reviewer subagent reads the workspace and the already-streamed tool arguments, then returns a structured allow/deny verdict with a reason. A reviewer crash or timeout denies rather than allows, and every decision reconstructs from the session log.

OpenBiliClaw

Discovery rather than search: it builds a model of your interests locally, then watches platforms and the open web on a schedule and reports back with sources.

Memento

Memory with an approval gate on writes and an audit surface afterwards. If you want an agent to remember things across sessions, this is the pattern to copy: bounded, layered and reviewable.

How we choose

The deciding question for this category is what happens when the agent is wrong. We prefer plugins that produce a reviewable artifact, a failing check, or an approval prompt over plugins that only promise better output. Autonomous loops without budgets and gates are excluded regardless of popularity.

How these six differ

They are not interchangeable skins on “agent.” Ouroboros and Aegis both police quality, but Ouroboros owns the whole execution contract while Aegis is a discipline layer you can put on top of other hosts. Agent Teams and Background Agents both spawn help; Teams is for structured parallel work you approve first, Background Agents is for long-lived workers you steer from the side. Auto Review is a gate on the action, not a planner — it decides individual tool calls, not the shape of the task. OpenBiliClaw is discovery, not autonomy. Memento is memory with an approval door — install it when the failure is forgetting, not when the failure is unchecked doing.

Stacking more than two of the gate-shaped plugins (Ouroboros, Aegis, Agent Teams) usually means three systems each think they own the task graph. Pick one primary control plane and let the others stay out of the completion path.

Sources & references

The technical claims on this page rest on the primary documents below. Each link is followed so it can be checked directly.

  1. [1]deepseek-ai/deepseek-harness — GitHubUpstream repository for DeepSeek Harness, the Cordis runtime and the plugin loading model.
  2. [2]Model Context Protocol — AnthropicSpecification for the MCP bridges several listed plugins implement.
  3. [3]dsh-plugin GitHub topic — GitHubThe discovery mechanism used to find plugins listed in this directory.
  4. [4]Keep a Changelog 1.1.0 — Keep a ChangelogThe changelog convention recommended for plugins that want maintainable release notes.

All links last verified 2026-09-11

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