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dsh-anchored-flash

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2026-08-17最近推送
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功能简介

Anchored-standard agent preset for DeepSeek Harness: Minimal-aligned first request, low-injection post-promotion, indirect AGENTS.md loading — anchored intelligence without the IQ drop. (DeepSeek Harness 的锚定标准预设:首轮 Minimal 对齐、晋升后低注入、AGENTS.md 间接按需加载——锚定智力不降智。)

✅
我们的评价
可用 — 实测通过,早期项目

Anchored-standard agent preset for DeepSeek Harness: Minimal-aligned first request, low-injection post-promotion, indirect AGENTS.md loading — anchored intelligence without the IQ drop. (DeepSeek Harness 的锚定标准预设:首轮 Minimal 对齐、晋升后低注入、AGENTS.md 间接按需加载——锚定智力不降智。) 实测能干净安装、正常启动。早期项目,但功能可用。

「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。

README

dsh-anchored-flash

English | 中文

An experimental DeepSeek Harness agent preset: Minimal-aligned anchoring with
low-injection post-promotion, an indirect AGENTS.md injection pattern, and
subagent anchoring
— the "anchored intelligence without the IQ drop"
experiment series.

Fork of xiaobright/dsh-anchored-standard
with local modifications; the experiment report is in
upstream issue #49.

Maintenance status (2026-08-17): upstream
xiaobright/dsh-anchored-standard
has entered maintenance mode (FAREWELL — the official API price change made
the experiment series cost-prohibitive). This repository, an experiment
branch of that series, is frozen: it no longer tracks upstream, and the
experiment conclusions live in
upstream issue #49.
Related work has moved to the zhu1090093659/dsh-web-ui ecosystem (the
non-assertive AGENTS.md hint, instructionHint, was merged there as #388).
Local installs keep working; no further releases are planned here.

What makes this different from upstream

Feature Upstream anchored-standard This preset
First request Minimal pair bash + str_replace_editor, maxTokens 1024, zero injected context same
System prompt after promotion complete: true persona, stays the Minimal sentence (46 chars) forever same, enforced by the assemble filter in every phase (tool-bootstrap)
Post-promotion catalog bootstrap pair + discovery tools + dev_tool_search unlocks configurable residentTools whitelist (default: 18 tools incl. memory/dtodo/web_search/de_session/read_image/exit_plan_mode/skill_search/skill_load)
instruction-hint wording imperative ("read the relevant instruction files first and follow them") — measured to flip the anchored trajectory back to "let me" neutral/suggestive reference note — measured to preserve "we" (see experiment table below)
Subagents opt-in includeSubagents default true — subagents go through the same anchor flow
AGENTS.md full digest injection (perturbs) or nothing indirect injection: 1 KB topic index + AGENTS-*.md topic files + env-* skills, read on demand (skill_load / read) — measured non-perturbing
Windows bash custom-bash (fixed path) custom-bash with PATH fallback when the configured Git Bash path is missing
Runtime context (memory snapshot etc.) stripped stripped in every phase (low-injection)

Experiment summary (measured 2026-08-16, DeepSeek V4 Pro, reasoningEffort=max)

Fingerprint = completed-reasoning counts of we / let's / let me
(case-insensitive, whole words). Sessions are real DSH sessions on Windows +
rc.6.

Exp Hint wording System prompt Result
baseline imperative ("read first and follow them") restored to standard (46→6620 chars) we→let me flip after promotion (0 we / 3 let me; model: "I must read relevant instructions")
E1 neutral reference note 46 chars in every phase we preserved (up to 49 we / 1 let me in 22.5k-char analyses)
E2 neutral + user asked to read AGENTS.md 46 chars full on-demand chain walked (skill_search → skill_load → read 1 KB index); we preserved; environment facts actually used
E1.5 suggestive ("reading the index is recommended") 46 chars we preserved; model reads only when the task needs environment facts

Key conclusions:

  1. The promoted system-prompt mutation (46→6620 chars) is itself a
    perturbation.
    Keep the system prompt at the single Minimal sentence in
    every phase.
  2. Imperative wording in a user-role injected message correlates with the
    style switch
    (we report correlation, not mechanism).
  3. Non-imperative reference wording does not flip the trajectory, and
    read willingness is driven by task need, not hint wording.
  4. Anchored intelligence and AGENTS.md availability are not mutually
    exclusive
    : tell the model (non-imperatively) that reference documents
    exist, and let it load them on demand.

Install

$target = Join-Path $env:USERPROFILE '.dsh\.agent-presets\anchored-flash'
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

Restart DeepSeek Harness, create a fresh session, pick 锚定标准·满血子代理
(anchored-flash). Do not switch presets mid-session.

Recommended AGENTS.md layout (the indirect-injection pattern)

Split the user-global ~/.dsh/AGENTS.md into:

  • ~/.dsh/AGENTS.md — ~1 KB topic index (3 iron rules + pointer table)
  • ~/.dsh/AGENTS-<topic>.md — topic files (environment / network / dsh /
    workflow / browser …)
  • ~/.dsh/skills/env-* — the same content as skills, discoverable via
    skill_search and loadable via skill_load

Verify

node verify/verify-anchored-flash.mjs      # 18 logic checks, no DSH runtime needed
node verify/trace-session.mjs <session-dir>        # header + reasoning fingerprint trace
node verify/count-pronouns.mjs <session-dir>       # we / let's / let me counters
node verify/dive-session.mjs <session-dir>         # full system + message sources
node verify/dump-session.mjs <session-dir>         # header + first-line dump

License

MIT. The preset is based on the DeepSeek Harness Standard preset and on
xiaobright/dsh-anchored-standard; see NOTICE and
LICENSE. Part of the experiment design and this documentation
were assisted by DeepSeek (an AI assistant); all measurements are from real
DSH sessions.

安装

🧩 让 Agent 自动装(推荐)

装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:

dsh plugin add dshbase-catalog

然后对 agent 说「帮我装 dsh-anchored-flash」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。

该插件是 GitHub 源码(未发 npm)——直接从仓库装:

Web profile:

dsh plugin --profile web add github:ruler770525/dsh-anchored-flash

Headless(CLI)profile:

dsh plugin --profile headless add github:ruler770525/dsh-anchored-flash

实测报告

验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。

使用场景

给 agent 网络能力——请求、API、代理或协议——让它能触达外部系统。

适合谁

任务涉及网络的人——调 API、抓资源或与远端服务通信。

二次开发建议

适配器和请求整形是缝——加协议、鉴权处理器、重试和端点抽象。

安全:尚未扫描——我们的每日静态扫描将很快覆盖它。

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