@klarkxy/dsh-self-improvement
Experience Learning：从结果证据中学习条件方法，并可选择将其导出为技能。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add @klarkxy/dsh-self-improvement@0.1.7Self Improvement 以 @klarkxy/dsh-self-improvement 发布，当前版本为 0.1.7。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
DeepSeek Harness learns how you want work done: what to do, under which conditions, what to avoid and how to check the result. Lessons live in the shared Memory store, which you have to enable explicitly; Dream — the context observation and consolidation mechanism inside @klarkxy/dsh-memory — owns vocabulary, author context and recent activity, and this package only creates procedural lesson records.
Requires Node.js ≥22 and DSH 0.1.7-rc.2, and no application-specific runtime packages are needed. On a standalone DSH Web host, install:
npm install @klarkxy/dsh-self-improvement
Install the public packages and explicitly enable Memory storage:
dsh plugin --profile web add @klarkxy/dsh-memory
dsh plugin --profile web add @klarkxy/dsh-self-improvement
This plugin never enables Memory or Dream on your behalf, and Dream can stay off. It adds no extra chat panel and no separate settings page. The bundle starts enabled and can be switched off independently. Review methods and Skill drafts under Settings → Long-term Memory → Experience Learning.
Settings → Plugins → Experience Learning carries its own settings row with an optional Extraction model menu for the extraction call; reviewing and counting methods here does not call Memory's model. A saved route is used for that call as an explicit model, while an empty selection follows the live session model and then the host default chat model. Only that call is affected, and a saved route selects a model — it is not evidence of connectivity.
New lesson records carry a structured procedure: origin (instruction or observation), goal, applicability conditions, recommended steps, actions to avoid and verification checks. Exceptions and original evidence are retained. Descriptive corrections are skipped, and mixed messages contribute only their method clause. One-off requests, fictional dialogue and quoted documents do not become durable methods.
Explicit human method requirements may become active immediately within their scope. Positive method feedback and correlated tool recoveries remain candidates until accepted, and acceptance means permission to use the method, not independent proof of its quality. Current instructions, task acceptance criteria and permissions always prevail.
A tool recovery requires the same human request, an explicit matching target and changed arguments. The same tool succeeding elsewhere, an unknown target or an unchanged transient retry is insufficient, and even a correlated recovery is an observation rather than verified task success. Silence and assistant self-reports are not evidence. Without AI, the fallback only preserves conservative explicit method instructions, never raw error narratives or word definitions.
Host pre-step injection uses native createUserMessage, preserves decision flags and inserts at most five active, unexpired, relevant lessons, about 800 tokens including the wrapper. Chinese retrieval is supported. On a continuation request, recent in-scope activity is read before selecting methods, independently of hook registration order. Disabling the plugin or losing Memory during an await stops injection.
Active methods can form a Skill Markdown draft with name/description frontmatter. Preview, acceptance, browser download and revocation remain explicit: no skill is installed automatically, and no AGENTS.md or executable script is changed. Download revocation only changes the application record, not files already downloaded. Legacy lessons remain readable without inventing new metadata or validation history.
The package has three entry points:
. — the Cordis plugin (name, inject, apply), the SelfImprovementEngine class and the shared constants CHAT_EVENTS_SLOT and SELF_IMPROVEMENT_RPC_CHANNEL. apply provides the engine as ctx.selfImprovement and registers the host RPC channel../contracts — browser-safe types and constants: the frozen AI/Memory interfaces from @klarkxy/dsh-plugin-kit, plus SkillRecord, ReviewSnapshot, LessonTrigger, injection bounds and the /dsh-self-improvement channel name../client — the review UI bundle. It provides the dshSelfImprovementReview render service that the Memory settings page embeds as its Experience Learning section.The host RPC channel is /dsh-self-improvement with endpoints status, extract, inspect, accept, reject, revoke, skill.preview, skill.accept, skill.reject, skill.revoke, skill.export, skill.exported and skill.unexport.