Plugins

Multi-provider wallet chip: official DeepSeek balance, per-session cost & tokens, third-party token totals, recharge shortcut, low-balance alerts.

Progressive tool disclosure: a deferred tool group costs one catalog line instead of its full schemas until the model loads it with tool_search, with one switch per group in Settings and each group measured against the live registry.

A DeepSeek Harness plugin for real-time token tracking and highly accurate session cost estimation, featuring dynamic peak/off-peak pricing support.

Activity heatmap in the DSH Web sidebar: GitHub-style grid of daily commits, token usage, and estimated spend, with a today stats line for all-session token totals, cache hit rate, and per-model auto-priced cost.

DSH Desktop enhancement plugin: it puts verifiable facts on the table. Constraints are injected only when relevant, so idle chat costs no extra tokens; injection is layered (session-stable text in the system prompt, volatile content as a tail snapshot) and the prompt cache stays valid. Discipline: each turn is classified (question / research / discussion / diagnosis / execution) with boundaries enforced - no file edits on question turns, no unsolicited fixes on diagnosis turns; citing code lines not opened this session, negative claims about unseen symbols, requirements that do not match the deliverable, and dressing up “I did not check” as “waiting for your decision” are all called out; replies are written for humans - a code, field name or id must be explained in plain words the first time it appears. Memory and knowledge: 75%/90% context warnings plus an exported session recap (say "continue" in a new session); project knowledge accumulated across sessions by working directory, auto-captured and deletable by id. Inspectable artifacts: task contract / change record (auto-logged, unverified items flagged at delivery) / hypothesis record (conclusions must pass an evidence gate) / design decisions. Dashboard and personas: routing, trigger hits and block assembly are written to lume-metrics.jsonl and queryable via lume_metrics; personas are distilled from chat logs, novels, scripts or character sheets, with long-term and temporary memory, a memory star map and persona card export/import.

Lazy-loading router for MCP servers: auto-discovers compatible MCPs and keeps only a shared router in the tool catalog, revealing a server's schemas when a turn needs them and hiding them again at turn end, so many installed MCPs stop costing context on every request. Falls open to normal visibility on any uncertainty, and the original MCP keeps ownership of execution, permissions and process lifecycle. Also supports explicit lazy connections with warm reuse, bounded reconnection, stdio and Streamable HTTP.

Session header badge showing DeepSeek peak/off-peak status, per-model token prices on hover, and real session/turn costs from actual usage.

A corner HUD for DeepSeek Harness that shows your session's token pressure, per-model cost, and daily/monthly usage at a glance, with an editable budget and balance that tracks spending for you. 右下角常驻的 Token 仪表盘：实时看会话压力、按模型估算花费。预算和余额点一下就能改，每天每月用了多少都有记录。

DeepSeek Harness plugin: 账户余额 + 会话费用（/balance /cost 命令、deepseek_billing 工具、Web UI 双胶囊），官方价格每 12 小时自动同步

DeepSeek API spend (current session and all sessions) and account balance in the aside panel, with official pricing and peak/off-peak support.

Three-tier now/next/later input planning dock for the DeepSeek Harness web GUI: a red/yellow/green priority strip replaces the busy-Enter queue, plain Enter queues to later, with in-place multi-line editing, drag reorder, and session-isolated freeze/resume; the freeze button bridges a separate plugin, [dsh-session-guard](https://github.com/drscrewdriver/dsh-session-guard) (installable from dsh-market), via stopNextTurn/resume RPC + composer lock for a real per-session lock, pairing with its global peak-hour auto-pause to stop sessions during DeepSeek's high-cost windows and resume off-peak.

Task-driven plugin equip engine: dual retrieval (curated rules + LLM semantic), combo scoring (synergy/conflict/cost/trust), conflict detection and install-command export.

Proactive scheduling: an adaptive heartbeat plus a value network (urgency, relevance, interruption cost) decides when the agent should speak unprompted.

DeepSeek Harness 插件:OpenCode Go 用量与花费悬浮仪表盘(配额、逐请求成本、模型/来源分布)

DeepSeek Harness (dsh) 插件：/cost 查看每个会话花费 + 可拖拽的悬浮费用胶囊

用于监控当前会话额度消耗、预估费用及当前API余额/Used to monitor the current session's quota consumption, estimated costs, and current API balance.

Shows DeepSeek balance and estimated daily spend, merges external vision-call JSONL records, and adds a per-session dashboard with model statistics, TTFT, cache rate, call logs, cost estimates, filters, and CSV export.

DeepSeek Harness (DSH) plugin: live conversation cost and DeepSeek account balance in the composer stats row — RMB in Chinese UI, USD in English UI

Token cost tracker for DeepSeek Harness -- track usage, calculate costs, budget warnings

Agent trajectory governance and anomaly diagnosis: rebuilds flat session logs into multi-branch trajectory trees, detects loop deadlock, invalid retry, and goal drift, alerts with cost attribution, one-click interrupt and breakpoint fork via official APIs, independent GUI tab.

Draggable grid-aligned workbench of 28 mini-cards in the margins of the conversation (API balance, token usage, cost, context pressure, todos, goal, usage heatmap, GitHub repo, image relay), with S/M/L/XL size tiers.

English edition of Weiwen's Law (KISS's Law): the first and only domain-agnostic white-box causal adjudication middleware for AI agents. Unlike domain-specific causal-inference tooling (statistics/economics/ML) or evidence-gated agent firewalls, it adjudicates *every* tool call along a deterministic structural causal chain (R->S->D->H->M) before execution - across any domain, with no training or per-domain tuning. It blocks destructive and credential-file operations, escalates repeated boundary violations, cuts faulting links until verified-fixed, and gives risk verdicts on un-auditable execution; runs fully local with zero API cost.

TypeSafe Jev (System One decision model) for DeepSeek Harness, end to end: jev_decision (choice/score/noul, parallel, typed answers + confidence), a Settings > Plugins card for the API key and switches, inline tool views showing every decision in the conversation (answer, confidence, latency, cost), an auto-guard (deterministic + Jev risk/loop checks), a local /jev dashboard, and an online verification benchmark (96.3% on 27 labeled questions, median ~283 ms on jev-latest, 2026-09-21). Honest by design: real API only, no mock fallback.

Peak/off-peak billing clock with a provider-neutral account readout (DeepSeek balance, subscription plan windows, relay credits), per-turn spend measured from the provider's own counter, and a /hist token-history scene split per provider for dsh-tui