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dsh-anchored-standard

Minimal first, full firepower second.

A two-stage preset: it opens in minimal mode to cut the noise, then switches to the full standard toolset mid-session. Community controlled experiments lifted the benchmark score from 91 to 98. Note: the author has stopped active development.

3,423 star Config / preset GitHub

Install

DeepSeek Harness 0.1.0-rc.5; Node.js 24. Note: the README states that active development has stopped because of rising costs, leaving maintenance only. Known pitfalls: a failed tool call still triggers session "promotion" (the durable tool/call event already exists); prefix-cache continuity breaks at promotion and after dev_tool_search is unlocked; the preset's permissions are equivalent to shell access; when the bootstrap tool is missing it falls back to the full tool catalog with only a warning.

A preset: copy the preset folder into your dsh presets directory, restart dsh fully, then pick it in a session.

Linux/macOS (run in the repo root)macOSLinux

dsh_home="${DSH_HOME:-$HOME/.dsh}" mkdir -p "$dsh_home/.agent-presets" test ! -e "$dsh_home/.agent-presets/anchored-standard" cp -R preset "$dsh_home/.agent-presets/anchored-standard"

Windows PowerShellWindows

$target = Join-Path $env:USERPROFILE '.dsh\.agent-presets\anchored-standard' if (Test-Path -LiteralPath $target) { throw "Preset already exists: $target" } New-Item -ItemType Directory -Force -Path (Split-Path -Parent $target) | Out-Null Copy-Item -Recurse -LiteralPath '.\preset' -Destination $target

Full tutorial

01Clone the repo locally

02Copy the preset directory to ~/.dsh/.agent-presets/anchored-standard (see the install command)

03Restart DeepSeek Harness completely

04Start a blank session and pick the "Anchored Standard (experimental)" preset

05Note: do not carry over sessions from other presets and mix them

Features

·Seven preset variants (base / zero-anchored / whoami / prefab / eternal-minimal / wire-think / combo) covering different anchoring strategies

·Two-stage tool exposure: a minimal bootstrap pair -> promotion to the resident tool catalog, with promotion state restorable across sessions through durable events

·The context-gate plugin controls context injection in one place

Voices

Reddit u/stealthispost · 2026-08-15

**Anchored Standard** (xiaobright/dsh-anchored-standard) does a clever hybrid: 1. First model request: presents V4 Pro with essentially the same environment as Minimal... 2. As soon as it makes its first real tool call/reply, it unlocks the full Standard toolset... The author found that the tool schema on that first request appears to be the decisive variable.

47 upvotes Source

Reddit u/for4f · 2026-08-15

the anchored standard result is the one that got me. 98/99 with the full toolset handed back after the first call kills the 'fewer tools = fewer mistakes' explanation, which was the obvious alternative. so it really does come down to what the model sees at init. kinda fits the RL story though. train a model inside one specific scaffold and it'll behave best inside that scaffold, first message included.

4 upvotes Source

Reddit u/somerussianbear · 2026-08-16

I saw the dsh-anchored-standard plugin yesterday, the popularity of this thing and what it promised, and decided to give it a try on porting the approach to a Pi extension, cause I really like that harness and wouldn't like to have a harness just for DeepSeek. It works, I managed to replicate the whole thing. All thinking uses "We ...", as flagged by xiaobright as being the trace of a superior version of DeepSeek v4 Pro.

9 upvotes Source

Reddit u/ZveirX · 2026-08-16

It's a gacha with the model as it is overfit to it. I have seen Bilibili experiments with it, minimal prompt, no system prompt, and even in minimal it often drops the "let me". There is just so many vocabulary the model has been trained on that it's inevitable that at times it begins to output distinctive patterns not akin to its original chain of thought—that's Entropy.

1 upvotes Source

Reddit u/PolychromeMan · 2026-08-16

Awesome. To be honest, I had to get ChatGpt to give me an explainer on this, but now that I have vague idea of what is discussed here...very interesting. A lot of my enthusiasm for AI development involves how the open-source community can use it, as opposed to more sealed off products released by frontier developers, so it's neat to see interesting potential that is more open-source friendly.

1 upvotes Source