Plugins

Live per-session cost badge in the DeepSeek Harness conversation header (top-right), with peak/off-peak (峰谷分时) pricing.

One installable DSH bundle with four independent plugins: the MCP Manager panel (which also drives the OAuth-enabled Streamable HTTP MCP client bridge), the Session Delete UI, the QQ bot bridge, and the per-model session cost meter.

A dsh plugin: after a timeout, the time distribution from the previous iteration is fed to the model, enabling the model to autonomously identify and adjust its behavior; if the introspection cost becomes too high, the plugin enters a dormant state, allowing the model to be restarted at any time.

DeepSeek Harness (DSH) 桌面版余额插件：悬停查看账户余额、红绿峰谷时段、Token 用量与每轮费用估算、消费记录、预算提醒和 CSV 导出。DeepSeek balance widget & cost tracker.

Hybrid model router for DeepSeek Harness: declarative rules, user-configurable cost control (cost-first / quality-first / balanced), optional LLM task classifier, and failure fallback chains.

Shows what each installed skill costs in the model context and hides a skill from the catalog without deleting it. Lists every skill found on disk with the exact catalog line the model receives (description normalized and truncated at the catalog cap), its body size and token estimate; previews the catalog message byte-for-byte as the agent will receive it, compares that with the copy already published in the current session, and reports skills on disk that never reach the catalog (invalid frontmatter, or shadowed by a higher-priority root). Hiding writes disable-model-invocation into frontmatter and keeps the file, so the skill still works via /name. Also imports skills from ClawHub, Skills.sh and GitHub URLs and uninstalls user-owned ones.

Notes-backed context compression for DeepSeek Harness: replaces LLM-summarized compaction with a model-written persistent notebook plus recoverable raw history, so the rollover boundary itself costs zero model calls.

Purges billion-context snapshots left behind after a session is deleted in DeepSeek Harness, and can also clean up cost-meter ledger rows (off by default).

Stops compaction summaries and session titles from burning their output budget on reasoning, by lowering the thinking level and raising the token floor for auxiliary calls only.

Reorder configured models in the composer model picker, set cache-hit, cache-miss and output prices per million tokens, and estimate per-turn and session costs with built-in DeepSeek peak/off-peak rates.

DeepSeek account balance above the sidebar account area, the running cost of the open conversation, the cost of each turn beside its token count, and a one-click AI breakdown for any turn above a token threshold.

Distill over-long model reasoning into its useful core, replay the compressed version on every later request, and report each session's cost and savings. Disabled by default: select one rewrite backend first. derive needs no install and works on packaged DSH; in-place needs 14 source patches and a rebuild (recommended for source checkouts); message-edit needs a third-party plugin and is experimental only.

Live multi-way tree of the current session's agents in the DeepSeek Harness conversation view and right sidebar, with status, plan progress, tokens, cost (requires dsh-cost-meter), and runtime on every card.

Adds a Teams sidebar dashboard that lists every Agent Teams chat with its roster and task roadmap, token spend in USD and RUB, work and online time, and an archive of older teams. Requires the Agent Teams plugin.

轻量化的QoL插件，可在助手消息元数据行追加本轮 token 费用估算（¥）。

Watches a turn's thinking and output streams and cancels the turn when the model starts repeating itself. Four detectors: a verbatim cycle, a counting loop whose lines differ only by a number, repeated lines separated by other text, and a user-supplied phrase list. A catch raises a manual-dismiss alarm card in the global overlay with an optional tone, and a Monitor tab holds the switches, thresholds and hit history. Detection is local string comparison with no model calls, so it costs no tokens.

Installs a self-evolving development-constraints rule library, exposes it to the agent through a constraints tool and a once-per-session reminder, and audits AI token cost and context usage.

Daily and weekly task manager: startup popup reminder, a marquee strip above the composer, one-click circle completion, editable task cards, and a Sunday AI weekly summary, plus a sidebar DeepSeek API usage widget with balance card, today/cumulative tokens and cost, per-model breakdown and a 7-day chart. Persists as JSON under $DSH_HOME.

Panel for MCP servers registered by @deepseek-ai/dsh-mcp-client: toggle each server on or off with live effect, see the registered tool count and estimated context-token cost of each server, and persist the choice to the home cordis.patch.yml with a timestamped backup before every write. The panel itself can sit either as a page inside Settings or as an icon row in the left sidebar, one seat at a time, with the switcher on the plugin page in Settings. Maintained fork of dsh-mcp-toggle.

Cost readouts for the composer, turns and sessions, a usage dashboard, daily/monthly budgets and settings, with DeepSeek balance from dsh-tally-balance-deepseek.

Per-request cost ledger covering retries and subagents, holiday-aware peak/off-peak pricing, shared pricing/usage/balance/budget services, and DeepSeek bill reconciliation.

Live estimated session spend in the composer dock, pricing each assistant step at DeepSeek's peak or off-peak rate for its own timestamp.

Cross-session usage rollup that resolves opaque route keys to real model names, with a per-request log, an editable four-bucket price table that leaves unknown models unpriced instead of guessing, and a calendar-day-filled bar trend whose values appear only on hover or keyboard focus.

Token statistics for every stored DSH session: a Host service folds the durable session logs into a persisted checkpoint and serves them over one read-only HTTP route, and the Usage settings page paints the saved aggregate immediately, then updates it in the background. Days are bucketed by hour behind a date picker, next to a trailing window with per-model breakdowns, request and web-search counts; no cost or pricing model.