Missher Evolution for DeepSeek Harness

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新手上手：Missher Evolution

为 Harness 提供 MSE SDK 的学习适配，保存有边界的工作流经验、偏好和可核验结果。

你需要知道的事	说明
插件包名	dsh-missher-evolution
当前源码版本	0.7.0
装好后在哪里使用	设置 → Missher Evolution
下载 / 源码	下载 0.7.0 安装包

安装、启用与第一次使用

1. 先从桌面端主页下载适合电脑的应用，完成模型配置。这个仓库是可选插件，不是独立桌面应用。
2. 阅读通用安装指南及本页原有安装说明，核对宿主与插件版本。桌面版使用“插件 → 添加插件”；Web/CLI 使用自己的目标配置组，不混用两种安装位置。
3. 安装后按宿主提示启用并重新加载，进入上表列出的入口。更新已有插件前保留配置和数据，不同时启用旧包名与新包名。
4. 先阅读 AGENT_INTEGRATION.md 核对宿主和数据版本，再检查设置中的学习状态。不要把两个产品线的数据目录互相覆盖。

使用前了解这些边界

这是既有 MSE 0.7 产品线的 Harness 分发包，和 Missher-MSE-Learning 的 alpha 产品线各自维护，不是同一插件的两个下载地址。

如果页面或功能没出现，先检查当前应用版本、插件是否启用以及加载错误。反馈时附版本、复现步骤和已脱敏错误；不要上传 API Key、真实会话、账号 Cookie 或学习数据库。Git 中的代码更新不会自动替换电脑上已安装的插件。

继续阅读

下文保留本插件的详细行为、配置、开发和验证说明。跨平台是否实际通过，以对应版本的验证记录为准；桌面安装包能启动，不代表全部插件和外部服务都已验收。

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dsh-missher-evolution is a prebuilt Cordis bundle for DeepSeek Harness Desktop >=0.3.8, using native lifecycle hooks or the optional Brain Hub service. Version 0.7.0 retains current eventAt-based session logs and evidence-bound registered methods, and belongs to the unified MSE release. It learns only bounded workflow categories, fixed preferences, closed outcomes, counters, hashes, and verified Chinese instructions. It does not train model weights or rewrite Harness, the plugin, or user projects.

It is the first production reference adapter for @missher/evolution-sdk. Cordis lifecycle events are translated by the Harness adapter, while selection, Capture, attribution, persistence, and maintenance run through the host-neutral SDK. The SDK is bundled into this plugin's generated Host code, so Harness users do not install or configure a second package.

The same JavaScript tarball runs on macOS Intel, macOS Apple Silicon, and Windows x64. There is no install-time build, native binary, external daemon, Python runtime, messaging connector, or remote analytics service.

Install

Public distribution: v0.7.0. The release tarball is byte-identical to the unified MSE 0.7.0 Harness artifact. See AGENT_INTEGRATION.md before installing on a new computer. Marketplace submission is separate from release publication; a release alone does not make this plugin searchable in DSH Market.

Install the prebuilt public archive after verifying the release checksum:

dsh plugin --profile <profile> add https://github.com/Missher12/Missher-DSH-Evolution/releases/download/v0.7.0/dsh-missher-evolution-0.7.0.tgz

Close the target host before changing an existing installation, and preserve a matched backup of the plugin, Profile configuration and $DSH_HOME/missher-evolution. Do not overwrite the experimental 0.1.2 review branch's data: its approval schema is incompatible with this unified release. Different Profiles in the same DSH_HOME still share evolution state; a separate Profile alone does not isolate that data.

Build and verify a local release tarball from this directory:

pnpm install --frozen-lockfile
pnpm run build
pnpm pack --pack-destination ./dist
node scripts/verify-package.mjs ./dist/dsh-missher-evolution-0.7.0.tgz

Install that tarball into the Harness profile that should use it:

dsh plugin --profile <profile> add <absolute-path-to>/dsh-missher-evolution-0.7.0.tgz

Harness activates the bundle for that profile. Open Harness Settings and select “Missher Evolution” to inspect status, enable or disable learning, review rules, or start a protected reset.

Here “review” means inspect rules. Version 0.7.0 does not expose per-rule reviewRule approval/revocation or a restore Remote; do not promise those APIs.

Verify

Inspect the composed profile without starting an agent:

dsh --profile <profile> --dump-config

The output should contain one dsh-missher-evolution bundle layer and one enabled missher-evolution Host entry. node scripts/verify-package.mjs <tgz> prints fixed JSON containing ok, file count, byte count, and SHA-256.

Runtime verification should use the Settings snapshot. Recall has one owner: when missherBrain exists it offers scoped handles; otherwise native agent/pre-step uses session.header.cwd and credits only its context message actually appended to the session. Rejected/canceled context is not an injection. eventAt is scanned within a bounded tail, with legacy event arrays still supported. Candidate evidence can create a Trial, but Active promotion additionally requires three supported treatment successes, two supported control observations, no treatment contradiction, and at least 0.15 observed uplift. These minimum samples do not establish statistical significance. Instruction rewrites start a new evidence epoch, and partial acceptance cannot be used to evaluate the trial. The Settings snapshot distinguishes recorded tasks from causal evidence.

Registered Methods

Accepted source-date and unknown-value checks can now retain bounded failure/repair case metadata. Maintenance proposes a compatible registered method using the existing AI budget or a clearly identified deterministic fallback. A separate fixed held-out evaluator tests failures, correct outputs and non-applicable inputs before the method can enrich an eligible local rule. These offline results never award Active status, real-task successes or measured model uplift.

After a trusted first failed file check, an existing next agent/pre-step continuation can receive one fixed repair hint. It remains within the user's original authority, does not itself write files, and requires a fresh native check. Read-only requests, Stop, closed turns, changed evidence, removed rules or exhausted budgets suppress the hint. There is no strict final-delivery blocker and no automatic final-turn restart. The Brain path also supports this bounded continuation without duplicating rule recall.

Portable templates use the SDK's explicit local operator interface. Only registered method IDs transfer; target scope, validation and reputation never come from the source host. Each target needs its own relevant evidence and local evaluation.

Data

Each Harness home owns an independent local directory:

$DSH_HOME/missher-evolution/

It contains schema-validated state, a bounded closed-event audit, a short-lived cross-process lock, and validated backups. Durable data never contains raw user messages, assistant responses, thinking, tool arguments, tool results, absolute paths, URLs, email addresses, credentials, or provider/model route names. Project identity is represented only by a SHA-256 scope hash; controlled semantic identifiers drive recall and duplicate consolidation.

The state is not shared with any other agent host. Model review uses only rule metadata and the most recent in-memory foreground route, and is skipped when no route exists. Store, classifier, lock, or advisor failures are fail-open and do not reject a normal Harness step.

Reset

In Settings, choose Reset and complete both confirmations. The Remote requires the exact current state revision and the literal confirmation RESET; stale or malformed requests are rejected. Reset clears learned rules and counters while preserving the current enabled preference.

Backup

A reset creates and validates a backup before replacing state. Scheduled maintenance also creates a backup before applying expiry, retirement, or a bounded advisor rewrite. The Settings response identifies the reset backup; backup contents remain local under $DSH_HOME/missher-evolution/backups/.

Do not edit or copy a live state directory between profiles. Stop Harness before performing any explicit offline backup or restore operation.

Uninstall

Remove the plugin from one profile with:

dsh plugin --profile <profile> remove dsh-missher-evolution

Uninstall removes the profile dependency and bundle layer. It intentionally preserves $DSH_HOME/missher-evolution so uninstall cannot erase learned data or unrelated profile/session content. Delete that directory separately only after Harness is stopped and any desired backup is verified.

Limitations

• The baseline is DeepSeek Harness Desktop >=0.3.8; missherBrain is optional. Compatibility is established by actual tests, not version comparison alone. Its packaged dsh interfaces remain within the declared >=0.1.0-rc.5 <0.2.0 peer range.
• Only direct foreground user turns are learned; subagents, internal work, plugin messages, scheduled work, and tool continuations are filtered.
• The plugin recognizes closed preference and experience allowlists and does not copy arbitrary correction text into durable rules.
• It improves future instructions and workflow reuse; it does not fine-tune or replace the underlying DeepSeek model.
• It does not import or synchronize state from another agent host.
• No process continues after Harness exits.
• Native smoke uses the real profile CLI plus controlled adapter events. It is not a measurement of autonomous model task improvement or a claim that every future host API is compatible.

Development

pnpm test
pnpm exec tsc -p tsconfig.json --noEmit
pnpm exec tsc -p tsconfig.client.json --noEmit

Official distribution

Source remains MIT. Existing official distribution policy and trademark policy continue to apply. Public availability does not grant third parties permission to present mirrors as Missher-endorsed releases. The public source export contains the Harness adapter and its bundled MIT TypeScript core, with provenance in SOURCE_PROVENANCE.json. It does not contain other host adapters or any live learning state.