Plugins

Side-by-side model comparison for the DeepSeek Harness Web UI: send one prompt to 2–4 models in sibling sessions forked from the current one, watch the answers stream in columns (tabs on phones) with latency, time to first token, tokens, and cost, then co

Nearly half the agent cost, with accuracy intact. Just enough tools is a DeepSeek Harness plugin that uses Jev to reveal tools and skills progressively. The main model starts with a clean planning step. Jev then selects which capabilities to add as the task unfolds.

TypeSafe Jev (modelo de decisão System One) para o DeepSeek Harness, de ponta a ponta: jev_decision (choice/score/noul, paralelo, respostas tipadas + confiança), um cartão em Settings > Plugins para a API key e chaves de liga/desliga, visualizações inline de ferramenta mostrando cada decisão na conversa (resposta, confiança, latência, custo), um auto-guard (checagens determinísticas + de risco/loop do Jev), um dashboard local /jev e um benchmark de verificação online (96,3% em 27 perguntas rotuladas, mediana ~283 ms no jev-latest, 2026-09-21). Honesto por design: só API real, sem fallback simulado.

Content-degradation detection (thinking loops, output repetition) for DeepSeek Harness, with a continue-vs-handoff cost verdict and zero-model handoff documents.

Go (weiqi) review coach: parses SGF records, backfills winrate and score analysis with a bundled KataGo engine, explains the costly moves in the chat, and writes the commentary back into an SGF copy; a web panel shows the board with problem moves, AI choices and variations.

Same-origin in mechanism with the two loudest lines in context compression. The code-skeleton gate follows the skeletonization approach of Headroom (Apache-2.0), whose published headline is 20% fewer tokens for coding agents and 60–95% fewer tokens for JSON, same answers. The estimator channel follows TokenPilot (arXiv:2606.17016), which reports up to 60% lower cost for long-session agents. Both figures are theirs, quoted as-is; this plugin ships no benchmark of its own and claims no reduction of its own. What it adds for DeepSeek Harness: choose a compression profile, set the Auto Compact trigger level and toggle code-skeleton compression from one settings section, with exact DeepSeek V4 tokenizer measurement, same-revision count verification, and fail-open behaviour that keeps the original tool results on unsupported models.

Session usage statistics panel: token and request stats at day/hour/minute granularity, an activity heatmap, bottom-bar session info takeover with per-turn cost chips, and cost estimation under multi-condition time-segmented pricing. Re-implemented from HaoyueQin/dsh-usage-statistics-panel with extensions.

Six independently togglable modules in one DSH plugin: per-turn CNY cost, DeepSeek account balance, PDF/Word/Excel/CSV read-write tools with right-sidebar preview, a compiler/runtime environment registry, and run/build tools that execute a program or an MSBuild project by environment id. Toolchain paths are resolved at run time (Visual Studio install-root scan, %ProgramFiles%, PATH) and can be overridden per environment through plugin config, so nothing is pinned to the author's machine.

Composer readouts for the DeepSeek Harness: CJK-weighted draft token count, session spend at official peak/idle rates, context occupancy, and what the same usage would have cost on the costliest other model; client-only, with no host half and no credential access.

Live token cost for every chat in the DSH Web UI: the chat, its subagents and the whole session tree, priced from a bundled models.dev snapshot of seven providers and 139 priced models, with cache read and write rates wherever the provider publishes them and DeepSeek from its own peak and off-peak table. Every finished answer carries its own price in the transcript, and a chat that is not currently open is priced from the log instead of disappearing. Spend is costed per interval from an append-only JSONL ledger in the project folder, so logged work keeps the tariff it was billed at. On top of it: budget-aware work plans packed against a money limit, routing scenarios that show which models are worth connecting, a generated plan document in English, Chinese or Russian, and a warning when spend belongs to no plan unit.

Shows DeepSeek peak/off-peak pricing status, a countdown to the next rate change, and the estimated session cost as inline text beside the model selector.

Team cost captain: meters every model call (subagents included), attributes each call to a member by workspace rules, prices it with the built-in DeepSeek 2026-09 catalog (peak/off-peak, CNY/USD) or user overrides, and appends it to a local JSONL ledger. Adds hot-reloadable member budgets, 80%/100% webhook alerts, optional over-budget enforcement, a team_cost_report tool with CSV export, and a settings-page team dashboard served over a Typert RPC service.

Automatic model-tier routing for DeepSeek Harness: one user instruction enters, one tier decision comes out — complex intent is planned on the strong tier and implemented on the cheap tier, simple intent stays cheap throughout, with a deterministic guard and a TTL escalation fallback.

Summarises the case evidence, diagnosis, repair procedure, parts list and cost-option comparison for a motor into a Markdown repair recommendation report with data provenance.

Combines historical supplier quotes and service rates into onsite-repair, factory-overhaul, green-remanufacture and replacement options for a motor, then recommends one by total cost of ownership.

Peak/off-peak billing cost dial for the DSH Web GUI: session token usage billed at the official DeepSeek peak and off-peak rates, a rate dial with a model-colored needle and switch countdown, a balance ring with a low-balance alarm, drag-to-resize, and a minimized status-lamp mode.

Local token usage and cost dashboard for DeepSeek Harness: four-segment token breakdown (miss/cache-hit/cache-write/output), cache savings estimate against the miss/hit price gap, per-session drill-down with context-growth curves and anomaly flags, global filters with shareable URLs, monthly budget progress with month-end projection, and day/month aggregate fast-path queries (O(days)) with incremental rescan.

DSH Web GUI plugin: first-position 【概览】tab in the right panel (context window / session metrics with active-only 1s runtime / per-model usage & cost analysis) plus a settings entry 【DeepSeek 开放平台】that opens platform.deepseek.com. Web profile only, theme-a

DeepSeek account-wide usage & balance panel from the official platform API (api/v0/usage/by_api_key): cache hit/miss & output tokens, cost, 24h–90d ranges, persistent platform token, and a model-visible `deepseek_usage_query` tool.

DeepSeek API balance + per-call cost tracker: durable per-call cost ledger from real usage chunks with official Beijing peak/off-peak (x2) pricing, 60 s balance polling, and a sidebar footer action showing balance and today's spend.

Composer stats strip for the DSH Web UI: official CNY pricing with auto-synced peak/off-peak tiers, per-model accounting, live timers, subagent-tree merging, DeepSeek account balance, budget alerts, and streaming cost estimation.

Dual-model auto-routing plugin: low-cost direct / high-cost upgrade with an escape-learning closed loop (wrong direct answers auto-learn fingerprints, force-upgrading the same fingerprint next time), persisted and interoperable with the Python ModelRouter.

Feishu/Lark channel that drives DeepSeek Harness agents from chats: streaming rich cards with live thinking and tool steps, per-turn cost metering at DeepSeek peak/off-peak rates, one-tap approval cards, model-gated image intake, and QR onboarding without a public endpoint.

A right-side session stats panel showing average cache-hit rate, session cost, runtime, request count, cumulative tokens and account balance.