Zian-anson/dsh-prompt-seed ↗★ 1
dsh-prompt-seed
将单行种子文本优化展开为具体提示词 适合需要一键扩写、优化提示词并保持语义不变的用户。
安裝
npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Zian-anson/dsh-prompt-seed說明文件
閱讀完整 README ↗Configuration
The row accepts a few optional keys; defaults are correct for almost everyone.
- insert:
- id: prompt-seed
name: dsh-prompt-seed
config:
route: /api/prompt-seed/optimize # route path (this is the default)
# provider: zai-coding-cn # pin the model route (provider + model
# model: glm-5.3-flash # work as a pair; defaults to agentDefaultModel)
# context: false # disable session-context injection (on by default)
Changing route requires editing src/client-plugin.js's ROUTE and rebuilding — the browser
half is a compiled bundle, so the two must be changed together. A test asserts they match.
| Key | Default | Meaning |
|---|---|---|
route | /api/prompt-seed/optimize | route path; changing it requires editing ROUTE in src/client-plugin.js and rebuilding |
provider + model | host default | pin the rewrite/audit model (both keys together) |
context | true | session-context injection; now read on demand (short draft or anaphora only) |
samples | $DSH_HOME/prompt-seed/samples.jsonl | event log path; false disables logging entirely |
templates | true | allow $DSH_HOME/prompt-seed/prompts/*.md to override the built-in prompts |
Depth is a client-side setting (right-click the ✦ button): auto (from local feedback counts),
light, standard, deep. It shapes how much a seed is unfolded — clarify and precise
ignore it. It is not a row config key because it is per-user, not per-profile.
Prompt overrides: drop system.md, user.md, audit.md, signal.md, deictic.md or
conversational.md into
$DSH_HOME/prompt-seed/prompts/ to replace the built-in contract. They are re-read on every
request, so an edit takes effect on the next click — no app restart.
Context injection sends the session's two most recent user turns (each truncated to
300 characters) to the rewrite and audit prompts as a reference-resolution-only block. The
last assistant turn is read only to anchor bare-signal inference ("42" → which option?) and is
never sent to the rewrite or audit prompts.
It fails open at every step — no session id, no sessionQuery service, corrupt reads, or
context: false all degrade silently to context-free optimization.
Model routing: rewriting rewards instruction-following over raw generation, but the
floor is higher than "any flash will do". Measured across providers (v0.4.6): glm-5.2
passes every case class cleanly — including the two gray zones where both flash-tier
models fail (procedural insertions into already-precise requests, and conversation
narration leaking into reference resolution). Flash models are fine for the simple
classes and cheaper, but the retry chain they trigger erases the latency win. The
tested-good route is one config line:
provider: zai-coding-cn, model: glm-5.2.