플러그인

한 세션의 실행을 턴, LLM 단계, 도구, 스킬, 서브에이전트, 코드 변경, 테스트로 이루어진 대화형 DAG로 렌더링하는 Graph 탭을 추가하며, 실시간 상태, 재시도 집계, 임계 경로, 트래젝터리 연결을 제공합니다.

피크 시간 자동 세션 게이트: 주말 모드 + 전역 피크 자동 일시 정지 + 세션 수준 동결/재개 + 백엔드 자동 재시도, 비피크 시간에 자동 재개.

Rewind / retry / fork 오케스트레이션(호스트) 및 conversation.chat.node 렌더러 교체(브라우저) — 사용자 말풍선의 메시지 편집/재시도 작업.

DeepSeek Harness 대화를 위한 턴 원자성 메시지 편집, 재시도, 리롤, 버전 트리 탐색.

SXS의 프로덕션 스크래핑 스택(일일 수백만 요청)으로 강화된 안티봇 HTTP 페치 도구: UA 풀 회전, 지수 백오프 재시도, 안티봇 월 감지(캡차/검증 챌린지), 적응형 레이트 리미팅 — 도구: `sxs_fetch` / `sxs_fetch_json` / `sxs_rate_status`.

After official llm-retry (n/5) gives up, keep retrying transient API failures (timeout, transport, rate-limit, 5xx, dropped SSE) on the same open step until success, cancel, or pause; AUTH, QUOTA, and user Stop are never retried.

Smart session titles for DSH: after each conversation turn an independent auxiliary LLM call summarizes the full user+assistant transcript into a title that follows the session's real topic instead of echoing the first message; the first message is titled instantly, failed built-in titles auto-retry on later turns, manual renames are never overwritten, and subagent/fork sessions are skipped.

Image generation workbench and agent tool for DSH: one tool (ark9_generate_image) paints text-to-image and image-to-image via any OpenAI-compatible API. Channels are entirely user-configured - no bundled endpoint, you bring your own baseURL, key and model name (manual input supported). Agent-initiated generations are approval-gated by default: requests queue in the floating panel and nothing bills until you approve; approval is non-blocking (the agent replies "awaiting your approval" immediately, and results, denials or timeouts are injected back so the agent reports them in the next turn). Floating glass workbench with five tabs (Generate / Approvals / Prompts / History / About), aspect-ratio grid with quality-budget + 16px-alignment sizing, transparent background, batch up to 10 images as aggregated sub-tasks, prompt library with custom JSON sources fetched through a host proxy, persistent generation logs with one-click retry, multi-channel aggregation with per-channel model fetching, bilingual UI (zh/en), stroke-SVG icon set, config import/export. Registers as a Better Sidebar tab when dsh-better-sidebar is installed; stacks above the dsh-cua FAB when both are present.

Auto-resume for interrupted agent sessions: an ordered rule table routes by failure type (rate limit, quota, auth, context overflow, crashed orphan) to automatic backoff retry, model switch, resume after context compaction, or a stop-loss notification, with a visual rule editor and a full activity log.

Session health-check: mechanically mines session logs into structured problem tickets (retry loops, tool-error clusters, interrupted turns, token waste) over the official session-query seam; works standalone.

Keeps long DSH sessions alive when a model channel starts failing: daruma takes over after the in-box retry gives up, trips a self-healing circuit breaker on repeated 429/5xx or a terminal error, and moves the next request to another channel in your chain. A panel beside the composer picks the backup by hand, switches show up as rows in the conversation, and every decision lands in a durable JSONL audit log.

Provider-first three-level model selector for the DSH Web model seat: pick a provider, then a model from that provider, with inline search on both levels, failed-provider retry rows, and a Model · Provider trigger.

Provider/model-aware adaptive pacing and visible rate-limit retries for DeepSeek Harness free models.

A permanent DSH plugin that bundles a developer workbench, an in-session conversation tree, and a plugin manager: build and run an LVAL project, browse its code, and keep per-program version snapshots with rollback; edit, retry, or branch any message in place, with message micro-versions; a feature manager plus a global-plugin library whose entries each carry an enable tier; cross-dialogue memory, one-shot temporary chats, and model collaboration; five network-permission tiers, mixed-model routing, a security audit, and browser control through a companion extension.

Fail-closed network recovery, recommended answers, and safe unattended continuation for DeepSeek Harness.

让 DeepSeek Harness 自动重试商汤 429/QUOTA 等瞬时网关故障直到任务完成——启动时给所有 llm-pi-ai provider 热注入加固版 retryPolicy。

DSH Web plugin for managing sessions: archive/unarchive, guaranteed physical deletion (transcript files + ~/storages/*.json sweep), drag-and-drop workspace reassignment, and branch-based message editing (edit/retry/reroll with reversible version timelines

Experience validation layer for DSH: zero-token collection of tool-failure/retry/search signals, AI refinement into verified skill books (three-layer verification), looked up at task start. Ships 10 trial skills and benchmark data (complex-task success 100% vs 60% bare).

Transparent multimodal routing for text-only models: every image in every model call is fully transcribed (verbatim OCR, data, uncertainty zones, injection-hardened) by your own multimodal understander, with focused re-look via vision_relook and automatic retry on image-related failures. No bundled endpoints, no borrowed logins.

Auto-retry failed API requests to keep DSH conversations going. Supports configurable status codes and error codes. 自动重试失败的 API 请求，让 DSH 对话不中断。支持自定义状态码和错误码。

When a dsh turn gets interrupted — by a web restart or an upstream hiccup (rate limit, 5xx, quota error) — this plugin auto-injects a "continue" so your session picks up where it left off, with a dead-loop guard that hands back control if the retry produces nothing.

DSH용 문자 깨짐 가드 번들: 쓰기 전 특징 기반 깨짐 감지와 검토 후 릴리스(동일 재시도는 통과), 실행 전 pwsh 인코딩 감사(ANSI/GBK/UTF-16/Default). Windows와 중국어 우선.

Keeps a redundant sandbox-escalation argument from failing a tool call. Escalating tools (pwsh, bash, write, edit) advertise the full sandbox_permissions enum, but DSH only accepts a level strictly wider than the one already in effect — a check its own source calls 'deliberately not a schema constraint'. A model that reflexively passes the argument therefore picks the level it is already at and the call dies before running with 'sandbox escalation to "workspace-write" is not strictly wider than this call's current "workspace-write" mode', costing some models a whole turn of retries. This plugin registers one tools/execute waterfall listener and, only on that documented rejection and only when the arguments really carried an escalation field, re-issues the identical call once without it. Safe by DSH's own documentation: the rejection precedes any execution ('nothing has run'), and the corrected call cannot match again, so the retry is loop-free. Reproduced and verified end to end — before: isError true, the command never ran; after: the command's real output, isError false, one tool/call and one tool/result. Zero dependencies.

Declare any number of LLM providers, each with its own endpoint, credential and per-model parameters (reasoning-effort vocabulary, image input, retry policy), across the OpenAI Chat, OpenAI Responses, Anthropic Messages and Google Gemini wire formats, configured from a settings page.