dsh-self-evolve

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-10-01），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

# dsh-self-evolve

[中文](README.zh-CN.md) | English

Hermes-style self-evolution for [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness): the agent saves proven procedures as skills, a background curator keeps the self-authored library healthy, and future sessions follow the proven procedure instead of rediscovering it.

## The loop

1. The agent solves a non-trivial problem (multi-step fix, hard-won root cause, user correction).
2. Prompt guidance nudges it to call `skill_manage(create)` with the proven procedure: steps, pitfalls, verification.
3. The skill lands as `//SKILL.md` — the exact directory-package shape `dsh-skill-filesystem` scans — so it enters the next session's skill catalog with **no extra wiring** and full progressive disclosure (catalog shows name + description; the body loads only on demand).
4. When a loaded skill turns out wrong, the agent patches it in the same session (`patch` is exact-text replace — token-cheap, like an Edit tool for skills).
5. The curator ages out what stops earning its place.

## Installation

Node.js 22.19 or later. Install the [npm package](https://www.npmjs.com/package/dsh-self-evolve) into a DSH profile (replace `web` as needed):

```bash
dsh plugin --profile web add dsh-self-evolve
```

Installing through `dsh plugin add` activates the bundled default configuration automatically. Verify the composed config without starting DSH:

```bash
dsh --profile web --dump-config
```

Install a local checkout instead of the npm release:

```bash
dsh plugin --profile web add /path/to/dsh-self-evolve
```

## What's registered

- **`skill_manage` tool** — actions `create` / `patch` (preferred) / `edit` / `delete` / `write_file` / `remove_file` / `pin` / `unpin`. Every write stamps `metadata.authoredBy: dsh-self-evolve` plus `createdAt` / `updatedAt` / `version`; only skills carrying that stamp can ever be modified — bundled and human-authored skills are read-only. `delete` archives (moves into the state dir), never destroys. SKILL.md is capped at 15 KB by default; resource files at 64 KB.
- **Prompt guidance** — one static system-prompt section (order 160) stating when to save, when to patch, and the memory-vs-skill rule ("skills store procedures; facts belong in memory"). Static text ⇒ cache-stable. Loads only where a `systemPrompt` service is composed.
- **Usage tracking** — a `tools/result` observer records every successful `skill` tool load of a skill living in this root into `/usage.json`. The ledger is separate from frontmatter so recording a use never rewrites SKILL.md.
- **Curator** — one pass per `curatorIntervalHours` (default 24 h, 30 s after startup): agent-authored skills unused for `staleDays` (30) get `metadata.status: stale`; unused for `archiveDays` (90) are moved to `/archive/-/`. Pinned skills are exempt; nothing is ever hard-deleted; foreign skills are never touched. Status writes restore the file's mtime so curation bookkeeping never counts as activity.

## Config

| key | default | meaning |
|---|---|---|
| `skillsRoot` | `/skills` | Where agent-authored skills are written (must be a scanned skill root). |
| `stateDir` | `/self-evolve` | Usage ledger + archive. |
| `staleDays` | `30` | Days without use before a skill is marked stale. |
| `archiveDays` | `90` | Days without use before a skill is archived. |
| `maxSkillBytes` | `15360` | SKILL.md size cap. |
| `maxResourceBytes` | `65536` | Per-resource-file size cap. |
| `curatorIntervalHours` | `24` | Minimum hours between curator passes; `0` disables. |
| `guidance` | `true` | Contribute the self-improvement prompt section. |

## Out of scope (by design)

Hermes layers two more mechanisms on top; both are deliberately separate systems:

- **LLM-review curation** (a forked agent voting keep / patch / consolidate / archive per skill) — the mechanical phase here leaves the hooks in place (`metadata.status`, the ledger, the ownership gate).
- **Offline GEPA evolution** (trace-driven optimization of skills proposed as PRs) — belongs in a pipeline that reads session logs (`ctx.sessionQuery`), not in the runtime plugin.

## License

MIT