Plugins

Turns the promises a chat quietly drops into an interest-bearing ledger: every “later” becomes a card, older ones rank higher, and each card jumps back to the conversation where it was said.

Hides opted-in third-party skills and MCP servers from the model-facing catalogs and serves them through one capability tool: search by intent, read the schema or the skill instructions, then call. A local journal records metadata only, never query text or arguments.

Adds a Polish button to the composer tool row right of the permission control: it reads the draft you have already typed, has the current model infer your intent and rewrite the draft into a clearer prompt, then turns the button into Cancel so one click restores the exact pre-polish text.

Exposes DSH as an MCP server so another agent can watch its thinking, tool calls and file writes in real time, share intent, take a floor lock that denies DSH's write/edit/git tools, inject mid-turn alerts, and delegate reviews.

Two games inside DeepSeek Harness where the model supplies intent and a local engine owns the rules: a twin-brain snake that periodically draws a strategy card, and Chinese chess where the model only comments on a move picked from locally generated legal candidates. Both keep running when the model is slow, offline or out of quota.

Zero-UI-overhead DeepSeek Harness plugin that automatically classifies conversation intents and names sessions with clean emoji prefixes (optimize, fix, feature, explore, etc.).

Real AST-based scan of installed plugins for malicious-intent patterns (dynamic eval, cross-plugin writes, exfiltration-shaped network calls), with an optional periodic schedule and auto-quarantine on critical findings.

One-shot DSH skill (SKILL.md) generator: capture intent, draft, validate, package and distribute skills from inside a DeepSeek Harness session (skill_new / skill_validate / skill_package / skill_improve_description).

An intent-calibrated DSH discussion mode that prevents complex conversations from drifting and turns them into evidence-based next steps.