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dsh-minimal-anchored

Verified · install-tested on dsh KDB-Wind

✓ Actively maintained

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2Forks
4Open issues
JavaScriptLanguage
2026-08-15Last push
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What it does

DeepSeek Harness preset: first round uses official Minimal tools, then unlocks full Standard. Reproduces higher-scoring We/Let's chain-of-thought in Project2 eval (Minimal 99/96 vs Standard 91/92), improves Let me behavior on Windows for DeepSeek V4 Pro.

✅
Our take
Works — verified, early-stage project

DeepSeek Harness preset: first round uses official Minimal tools, then unlocks full Standard. Reproduces higher-scoring We/Let's chain-of-thought in Project2 eval (Minimal 99/96 vs Standard 91/92), improves Let me behavior on Windows for DeepSeek V4 Pro. It installs cleanly and boots without issues in our testing. It's early-stage but functional.

“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.

README

dsh-minimal-anchored

中文说明

An experimental DeepSeek Harness preset. On the first request it shows the model
the same two tools as DeepSeek's official Minimal preset, persistent bash and
str_replace_editor, with the Minimal system prompt, a 1024-token output limit,
and no injected workspace or skill context. Once the session makes its first
tool call or writes its first reply, the full Standard tool catalog opens up.

This is a community project. It is not an official DeepSeek preset and is not
affiliated with or endorsed by DeepSeek.

Why this exists

DeepSeek V4 Pro pays a lot of attention to which tools it can see in the API.
Upstream also reported Project2 V4.1b scores on this endpoint: the official
Minimal preset scored 99 and 96, while Standard and PTC scored 91 and 92, and
the higher-scoring runs showed the we/let's reasoning style. This preset
copies Minimal's first-request tool identity.

The upstream experiment
xiaobright/dsh-anchored-standard
bootstrapped the first request with pwsh/bash + read, a 1024-token output
cap, and stripped injected context. Its
issue #11
then ran controlled Windows tests and found that the tools shown on the first
request matter most:

First-request tools Source n First line let me
persistent bash + str_replace_editor official Minimal preset 5 5/5 We need... 0.0
pwsh + read anchored-standard 8 8/8 The user wants / Let me... 2.0 to 2.6

This preset keeps that approach and changes only the first-request tool surface.
It mounts the official Minimal persistent-shell and editor groups, so request #1
sees bash + str_replace_editor. The 1024-token cap and the first-request
context filter stay. After promotion the session gets the full Standard catalog
plus those two tools.

How it works

  1. Keep the Minimal system prompt:
    You are a helpful software engineer assistant.
  2. On the first model request, expose only the official Minimal tool schemas:
    persistent bash and str_replace_editor.
  3. Strip auto-injected context on request #1: the AGENTS.md/CLAUDE.md workspace
    digest and the available-skills reminder that true Minimal never mounts
    (suppressedContextSources). Skill gestures the user sends themselves are
    not filtered, and both injections come back from request #2 on.
  4. Cap request #1 at bootstrapMaxTokens (default 1024), then release the cap
    after promotion.
  5. After the first durable tool/call or the first assistant/message, expose
    the full Standard catalog. Request #1 always sees the bootstrap catalog and
    request #2 always sees the full one.
  6. Derive the phase from durable session events, so resume and reload keep it.

Results

Local tests on Windows 11 with opencode-go, deepseek-v4-pro, and
reasoningEffort=max, 2026-08-15. Counts match upstream: completed reasoning
text, case-insensitive, whole words.

Preset Prompt language First-request tools maxTokens we let's let me
dsh-anchored-standard (real session) Chinese pwsh, read 1024 0 0 5
dsh-anchored-standard (control) English pwsh, read 1024 3 2 0
dsh-minimal-anchored #1 English bash, str_replace_editor 1024 2 1 0
dsh-minimal-anchored #2 English bash, str_replace_editor 1024 3 1 0
dsh-minimal-anchored Chinese bash, str_replace_editor 1024 0 0 1

One more Windows session, reported by a user but not counted line by line, used
only we/let's reasoning and no let me.

A few limits worth knowing:

  • we, let's, and let me are trajectory fingerprints, not performance
    claims. Matching the wording does not promise a score or capability change.
  • English prompts reproduced reliably in the tests above. Chinese prompts do
    not produce a stable English we fingerprint; see upstream issues
    #6 and
    #11.
  • The model endpoint can drift over time. Treat these numbers as a snapshot,
    not a contract.

Compatibility

Developed and tested against:

  • DeepSeek Harness 0.1.0-rc.5
  • repository commit 47f9438
  • Node.js 24 on Windows

DeepSeek Harness is a developer preview and explicitly permits breaking
changes. Check the upstream composition before using this preset with a newer
release.

On Windows the bootstrap shell is persistent bash. Make sure a bash is
available (Git for Windows or WSL, for example) before starting a session.

Install

Clone this repository and copy the whole preset directory into the user
preset root under the id minimal-anchored.

PowerShell:

$dshHome = if ($env:DSH_HOME) { $env:DSH_HOME } else { Join-Path $env:USERPROFILE '.dsh' }
$target = Join-Path $dshHome '.agent-presets\minimal-anchored'
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

Linux/macOS:

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

Restart DeepSeek Harness completely, start a blank session, and select
Minimal Anchored Standard (experimental). Do not switch presets in a
session that already has content.

Verify

Export the session JSONL and inspect request/header events:

  • the first header should contain only bash and str_replace_editor, with
    config.maxTokens: 1024 and the Minimal persona system prompt;
  • the first request's messages should contain no AGENTS.md/CLAUDE.md digest and
    no available-skills reminder;
  • after the first tool call or first assistant reply, the next changed header
    should contain the full Standard catalog (plus bash and
    str_replace_editor);
  • later requests keep that full catalog and restore the standard context
    injections.

Run the local zero-dependency tests:

npm test

Behavior worth knowing

  • With the default promoteOn: either, the session promotes after its first
    durable tool/call or its first assistant/message, whichever comes first.
    Set promoteOn: tool-call to require a tool call.
  • A failed tool execution still promotes the session because the durable
    tool/call already exists.
  • If a bootstrap tool is missing, the preset degrades to the full catalog with
    a one-time warning instead of failing requests. Invalid promoteOn values
    fail when the preset mounts.
  • While a session is unpromoted, the pre-step filter strips messages whose
    source.kind is listed in suppressedContextSources (default:
    agent-instructions and skill-catalog). Set the list to [] to turn the
    context filter off. If the filter itself fails, it keeps every message.
  • The tool catalog changes once, so request-prefix cache continuity changes
    once too, between the first and second model requests.
  • The preset has the same trust level as shell access. Read its files before
    installing it.
  • The plugin makes no network requests and adds no telemetry.

Attribution

This project is derived from
xiaobright/dsh-anchored-standard
at commit 6472c1c, with the first-round budget-cap listener fix synced from
upstream PR #13 (commit c774e60). That project is based on the DeepSeek
Harness Standard preset. The Minimal persistent-shell and editor groups are
copied from the official DeepSeek Harness Minimal preset. Copyright and license
details are in LICENSE and NOTICE.

License

MIT. See LICENSE and NOTICE.

Install

🧩 Let your agent install it (recommended)

Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:

dsh plugin add dshbase-catalog

Then say "install dsh-minimal-anchored for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.

This plugin is GitHub source (not published to npm) — install it straight from the repo:

Web profile:

dsh plugin --profile web add github:KDB-Wind/dsh-minimal-anchored

Headless (CLI) profile:

dsh plugin --profile headless add github:KDB-Wind/dsh-minimal-anchored

Test report

Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.

When to use it

Run dsh as a native desktop app — its own window, tray icon, and shortcuts — instead of a browser tab.

Who it's for

Users who want an installed-app feel and system integration (tray, global hotkeys, auto-launch) on their OS.

For developers — extending it

The native shell is the seam — add global shortcuts, notifications, single-instance locking, or OS-specific behaviors.

Security: not yet scanned — our daily static scan will cover it shortly.

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