Plugin

Lettura di saldo/utilizzo ancorata al composer per DeepSeek, Kimi Coding, OpenCode Go, Zhipu, MiniMax, OpenRouter e OpenAI Codex — basata su provider, polling di 2 s, cache di 5 min.

Uno sciame a matrice di subagent che instrada attività eterogenee al modello più adatto da un gateway in stile OpenRouter più cfgpu.com/llm/square, invia ciascuna tramite subagent in-process o chiamate LLM dirette e traccia il consumo di token per modello con un ranking guidato dal feedback.

Un plugin meta-agente nativo del modello per DeepSeek Harness: il modello sintetizza a runtime flussi di lavoro specifici per il task a partire da cinque pattern di workflow agentici (concatenazione di prompt, worker paralleli, router, supervisore, ciclo di valutazione) e coordina strumenti e subagent

On-demand skill tools for DeepSeek Harness: registers skill_search / skill_load / skill_ref so the model searches a staged skill library first and loads a skill body only when it needs it, keeping the library out of the resident session catalog and out of every turn's context; adds a Skills tab to the conversation view ring that reads back the whole session and lists which skills were actually loaded, and in which turn. Zero dependencies, and the records render client-side only, never entering the model's context.

Call TypeSafe Jev / OpenRouter System One for noul, choice, and score (jev_ask / jev_check / jev_rank).

Multi-provider LLM API balances under the chat input, with presets for DeepSeek, OpenRouter and SiliconFlow.

Fronts stdio MCP servers with three router tools (list_capabilities, describe_tool, call_tool) so schemas load on demand instead of riding every request; shapes every tool result through a deterministic output ladder that archives the original first (retrieve_spill reads it back); prices tool groups in tokens and can hide built-in groups per agent. Bridges to a standard-library Python router, so Python 3.9+ is required.

One settings page that lists every subscription sign-in the harness can offer and walks you through it — ChatGPT (Codex), Claude, GitHub Copilot, OpenRouter, Kimi and xAI — reading the list from the authorization seam instead of hardcoding providers, and showing credential records no registered flow claims any more.

Multi-platform LLM balance and quota panel: configure DeepSeek, OpenRouter, Kimi, Zhipu GLM, MiniMax, NewApi or custom endpoints, poll on a schedule, draw balance and quota trend charts, and push threshold and window-reset notices through multiple channels.

Live speech-to-text dictation into the dsh web composer via OpenRouter STT

FreeDSH — free-first multi-model routing, safe core updates and pt-BR/Windows support for DeepSeek Harness. Installable as a DSH bundle (dsh plugin add). Unofficial project.

Beginner panel for DeepSeek Harness: routes a plain-language request into ready-to-use plans (prompt variants, matching skills, advanced moves) with a local keyword engine and fills the chosen plan into a new session in one click.

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.

Balance badge that follows the active model provider: official readings for DeepSeek, Qwen Token Plan and Aliyun BSS, plus Moonshot and OpenRouter endpoints not yet key-verified.

Product Design workflow suite for DeepSeek Harness - a router plus nine pd-* skills carrying ideas from a minimum design brief through visual directions, evidence-grounded research and audits, URL cloning, frontend builds and a blocking design-QA gate.

Installs a skill-router skill that semantically searches a local skill corpus on demand, keeping the corpus out of the per-turn model catalog.

Text-to-image and image-to-image generation via OpenRouter's unified Image API: configurable model aliases with parameters gated against the live model capability listing, reference-image inputs, a settings card, and inline chat display of results.

Rule-based multi-provider model routing for DeepSeek Harness with pre-first-token failover, cooldown circuit-breaking, usage accounting, and a status API.

Global Alt+M model command palette for DeepSeek Harness Web: fuzzy search over models and providers, favorites and recents, per-model reasoning effort, provider and model configuration, request retries, capacity presets, and optional OpenRouter image/video generation tools.

Free-tier model aggregation for the DeepSeek Harness (dsh): registers the freeroute provider over a pool of free-quota upstreams (OpenCode Zen / B.AI / OpenRouter / SenseNova built in, plus remote catalogs and custom gateways), transparent failover before

Adaptive model discovery, evaluation, tiering, and subagent routing for DeepSeek Harness.

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.

Free-tier model routing for the DeepSeek Harness (dsh) - discover OpenRouter free models, apply the best free model as agent default, auto-rotate on rate limits; paid config untouched unless asked.

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.