dsh-a-share-screener
面向 DeepSeek Harness (dsh) 的 A 股选股插件：基于免费 Eastmoney 数据源支持可插拔策略，并采用可扩展的数据源抽象。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:Gaines-cz/dsh-a-share-screener#e78938ece6d203b1573a09b98fae094705c3babcA Share Screener 以 dsh-a-share-screener 发布，当前版本为 0.3.0。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。
An A-share stock-screening plugin for DeepSeek Harness (dsh): strategies composed from reusable atomic filters on free, token-less data sources, behind an extensible data-source abstraction.
This is a technical screening tool for historical price/volume patterns. It is NOT investment advice.
Requires the dsh CLI (DeepSeek Harness).
dsh plugin --profile myprofile add github:Gaines-cz/dsh-a-share-screener
Git installs pull source, but the prebuilt lib/ output is committed to the repo, so no build script runs at install time. Pin a commit (github:Gaines-cz/dsh-a-share-screener#<sha>) if you want immutability.
Start with the profile:
dsh --profile myprofile
Ask the agent in natural language:
List the available screening strategies. Screen all A-shares with low_flat_limit_up, minDrawdownFromHigh 0.7.
Three tools are registered:
| Tool | Purpose |
|---|---|
a_share_list_strategies | Strategy ids, descriptions, parameters, defaults, valid ranges |
a_share_list_filters | Atomic filter ids, descriptions, parameters, defaults, valid ranges |
a_share_screen | Full-market scan; returns candidates with quantified evidence |
The first full scan downloads history into a local disk cache and can take many minutes (bounded by the data source's rate limit); later scans reuse the cache and only fetch new trade dates. Cancellation is cooperative — aborting the tool call stops the scan.
flat_base_low"Bottom + flat base": the stock trades at or below the 15th percentile of its recent price distribution (~3 years, clamped to available bars) while the last month is a flat, MA-converged base. No limit-up pattern is required. Pair it with minListDays / maxListDays to constrain listing age — e.g. minListDays: 365 + maxListDays: 1460 screens stocks listed 1–4 years.
low_flat_breakout"Deep low + near-bottom volume breakout" — the right-side twin of low_flat_limit_up: deep below the window high (default ≥ 65% drawdown) while staying near the window low (low ≥ 40 bars back, price ≤ 50% above it), a volume-heavy day (≥ 2× the prior 5-day average) closed ≥ 2% above the high of the preceding one-month flat base with the price holding out of the base since (default ≥ 2 confirming closes), and the MA20 stopped falling with price at or above it. Deliberately no low_percentile gate: a breakout close above the base high sits at the top of the bottom-side distribution by construction.
low_flat_limit_up"Historical low, flat base, faded volume-heavy limit-up": the stock sits deep below its window high (default ≥ 65% drawdown) at the bottom of its recent distribution (≤ 15th percentile of ~3 years), the last month is a flat, MA-converged base, and within ~6 months there was a limit-up day on ≥ 2× the prior 5-day average volume that has since pulled back below its close while volume cooled to ≤ 40% of the limit-up day.
All thresholds are per-call parameters with defaults (see a_share_list_strategies). Board-aware limit-up thresholds: 10% main board, 20% ChiNext/STAR, 30% BSE. All price-level math runs on a chained daily-return index, so splits and dividends cannot fake a crash or a bottom. Universe filters (all configurable): ST/delisting names, BSE, listings younger than minListDays (default 365) or older than maxListDays (default 0 = no upper bound).
All strategies are compositions of the atomic filters below.
Every strategy is a declarative predicate over reusable atomic filters, combined with AND / OR / NOT into an expression tree. Fifteen filters ship today (a_share_list_filters lists them with their parameters):
| Filter | Gate | Needs |
|---|---|---|
deep_drawdown | latest price ≥ X% below the window high | — |
low_percentile | latest price ranks ≤ Xth percentile of the window | — |
bars_since_low | the window low lies ≥ N bars back while price stays near it | — |
flat_base | recent window is flat with converged MAs | — |
platform_breakout | a volume-heavy close cleared the preceding flat base's high and held | — |
ma_stabilization | the MA stopped falling (slope ≥ X) and price sits at/above it | — |
volatility_regime | annualized realized volatility inside [min, max] | — |
volume_limit_up | a volume-heavy limit-up day exists in the window | — |
cooldown_pullback | price pulled back below that close and volume cooled off | — |
volume_dry_up | absolute volume drought: recent average ≤ X% of the preceding baseline | — |
industry_clearance | the industry board itself is in deep clearance (median member drawdown / deep share) | industry (all shipped sources) |
industry_position | the industry board sits low in its own range (median member window percentile) | industry (all shipped sources) |
market_cap_band | total market cap inside [min, max] 亿元 | marketCap (all shipped sources) |
amount_liquidity | median daily traded value ≥ X 亿元 | amount (eastmoney only) |
turnover_band | median daily turnover inside [min, max] % | marketCap (all shipped sources) |
Filters that need a capability the active source lacks refuse to run — the scan aborts loudly with the missing capability named instead of silently degrading.
a_share_screen also accepts a predicate (mutually exclusive with strategy): a small JSON DSL over the atomic filter ids, e.g.
{ "all": ["deep_drawdown", { "any": ["platform_breakout", "volume_limit_up"] }] }
Groups are { "all": [...] } (AND), { "any": [...] } (OR), { "not": … } (NOT); leaves are filter ids from a_share_list_filters; max depth 3, max 12 leaves. params tunes the composition exactly like a registered strategy. The CLI equivalent is --predicate '<json>'. Strategies using industry_clearance trigger a market-wide aggregation pre-pass; its per-board statistics (median drawdown, deep share, members) appear in each candidate's evidence.
Composition runs one shared derivation pass per stock (chained return index + pre-computed limit-up days), then evaluates the tree: a short-circuit pass for strict hits and a full pass that produces per-gate metrics for the tiered report — which is how "near-miss" candidates (one gate short) are surfaced.
Three free, token-less sources ship today; sina is the default (its 前复权 closes match market prices).
| Source | Token | Notes |
|---|---|---|
| Sina (default) | none | 前复权 daily bars, 1023 bars per request; the recommended primary |
| Eastmoney | none | back-adjusted klines per stock (the only source with per-bar amount); clist host fails over realtime → delayed |
| Tencent | none | 后复权 fallback (report prices run high); backup only |
The stock list (with industry + market caps) comes from the shared Eastmoney clist endpoint for all three sources.
Every adapter sits behind a DataSource interface (src/datasources/types.ts); the screener, tools, and plugin entry import only that interface, never a concrete vendor. Cache lives under $DSH_HOME/a-share-screener/<source-id>/ (override with cacheDir).
To support another vendor later, implement DataSource and register it in src/datasources/index.ts:
// src/datasources/my-vendor.ts
import type { DataSource } from './types.js'
export function createMyVendorDataSource(limiter: RateLimiter): DataSource {
async function listStocks(signal: AbortSignal) { /* → StockMeta[] */ }
async function dailyBars(fullCode: string, startDate: string, signal: AbortSignal) { /* → Bar[] */ }
return { id: 'my-vendor', capabilities: { industry: false }, listStocks, dailyBars }
}
add myvendor: createMyVendorDataSource to FACTORIES. Set capabilities.industry: true (and populate StockMeta.industry) if the vendor can classify sectors.
Set in your profile's cordis.patch.yml (all fields have defaults):
- replace:
- id: a-share-screener
config:
# cacheDir: /path/to/cache # optional, defaults to $DSH_HOME/a-share-screener
dataSource: sina # sina (default) | eastmoney | tencent
requestsPerMinute: 200
historyBars: 800
scanTimeoutMs: 1800000
excludeST: true
excludeBSE: true
minListDays: 365
maxListDays: 0 # 0 = no upper bound; e.g. 1460 ≈ 4 years
The preferred way is composing existing atomic filters into a predicate tree — no screening code to write, per-gate diagnosis comes for free:
// src/strategies/my-strategy.ts
import { composeStrategy } from '../engine/compose.js'
import { createFilterRegistry } from '../filters/index.js'
export const myStrategy = composeStrategy({
id: 'my_strategy',
description: 'What it looks for, model-facing.',
// deep drawdown AND flat base (no limit-up requirement this time)
predicate: {
kind: 'and',
children: [
{ kind: 'filter', filter: 'deep_drawdown' },
{ kind: 'filter', filter: 'flat_base' },
],
},
filters: createFilterRegistry(),
})
For shapes the atomic filters do not cover, implement the Strategy interface by hand (screen returns a hit or null; an optional diagnose powers the tiered report). New atomic filters plug in through src/filters/index.ts with the same Filter interface the built-ins use.
Either way, register it in src/index.ts next to the built-in one — no other changes. The tool schemas and a_share_list_strategies pick it up automatically.
The same code ships a standalone command-line tool: manual trigger, local bar cache, free multi-source data (Sina primary / Eastmoney fallback / Tencent backup), no token.
pnpm install
pnpm sync # incremental local cache sync (weekly); default full market, narrow with --board / --codes
pnpm scan # tiered report: strict hits + near-miss candidates, each with gate-level metrics
pnpm strategies # list strategy ids and their parameter tables
pnpm filters # list atomic filter ids and their parameter tables
pnpm sources # list data source ids
Common options: --source sina|eastmoney|tencent, --board <name> (e.g. --board 核能核电), --codes 600519,000858, --strategy <id>, --params k=v,k2=v2, --min-list-days <n>, --max-list-days <n> (0 = no upper bound), --cache-dir <dir>, --out <dir>.
pnpm scan writes reports/<date>-<strategy>-<scope>.md (+ .json). The near-miss tier (exactly one gate failed) exists because a strict multi-gate strategy frequently returns zero hits — it keeps every run reviewable.
f100 on the shared stock list — all shipped sources expose it via capabilities.industry), not the SW (申万) L1/L2 scheme; industry_clearance aggregates on it. Separately, --board screening uses the Eastmoney industry/concept board-member endpoint.MIT