Plugins

Session cost chip in the DeepSeek Harness conversation header showing live token usage by bucket, peak/off-peak tariff pricing, and a countdown to the next tariff switch.

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.

Shows MiniMax Token Plan usage in the Settings page through webServer routes and reads either subscription key name from environment or credentials file.

DeepSeek Harness 插件：生成前注入「人味」风格约束 + AI 味检测报告（纯代码、零 token、结果可复现）。dsh plugin: human-flavor style injection + AI-flavor detection report, judged by code.

精准 Token 洞察，实时追踪，智能优化提示和用量归因 Sharp token insights, real‑time tracking, smart optimization signals & attribution

Context-window attribution for DSH Web: a Mini Utility Dock panel that ranks the user messages, assistant turns, reasoning blocks and tool results of a session by the tokens each one occupies, so it is clear which entries hold the window. It also shows the share by entry type, the heaviest entries across the live sessions of the host, and, where the host provides them, provider usage and the estimated system/tools/messages composition. The panel is read-only: it does not estimate cost, modify a session, or trigger compaction.

a plugin of token insight for deepseek harness.

DeepSeek Harness plugin: per-day token usage statistics — 13-week heatmap, stacked daily chart, /token-usage command

ServerChan3 (Server酱) push notifications when a turn finishes — title, model, project directory, git branch, status and a reply excerpt, with subagent filtering and fire-and-forget delivery.

Git Changes tab for the DSH web GUI: staging, diffing, AI-drafted commit messages, branch/merge/stash/worktree operations and sync, with live updates via fs.watch plus a changeToken poll.

Multi-agent isolated debate for DeepSeek Harness: debaters of different temperaments research independently (no herding), then cross-examine, then judges converge to a conclusion. Runs as a background job with per-agent progress, token accounting, wave-parallel execution, and session-referenced resume.

Input redundancy pruning for DeepSeek Harness — drop repeated/redundant tokens before they reach the model (layer ②).

Context compaction / headroom for DeepSeek Harness — compress the live context so the prompt stays small without losing the state that matters (layer 3).

Session context handoff for DeepSeek Harness — stop re-reading and re-deriving context every session. A single skill (layer ①) that keeps the next session warm.

Terse prose for DeepSeek Harness — compress the agent's own output so every reply costs fewer tokens (layer 4). Style, never substance.

Resolves unique kebab-case skill substrings in slash tokens, so /oneshot can load game-package-oneshot.

Automatically sends a "continue" prompt when a reply is cut off at the output token limit, resuming long answers without manual input; aimed at self-hosted Ollama deployments with small output caps.

Token-efficient persona runtime for DeepSeek Harness with local catgirl rendering and progressive tool-schema disclosure.

Qwen Token Plan CN Responses provider for DeepSeek Harness via the OpenAI Responses API, with Qwen server-side tools, DSH local function tools, text/reasoning/tool-call multi-turn history, persisted image attachments, and a per-release official model catalog snapshot.

Persistent token-usage ledger and Web Usage dashboard for DeepSeek Harness.

Token usage statistics by model, session and date in a sidebar panel, plus OpenCode Go quota, DeepSeek balance and Z.ai quota monitoring.

Real-time token estimates for the DSH conversation composer, combining the current context baseline with the draft and showing exact or heuristic counts.

DeepSeek Harness plugin that aggressively saves tokens without affecting task quality: lossless head/tail truncation of tool results (default), grep-result folding, pressure-triggered dsh-compaction-basic delegation, and an LLM-summary CompactionEngine subclass for the aggressive mode. Saves 97.6% of input tokens on an 8-scenario synthetic suite, with all reductions routed through dsh event flow so model-visible = logged stays intact.

Token usage dashboard for the DSH web GUI — today/week/month totals, per-model breakdown and a stacked 30-day chart, with a 4-language UI.