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dsh-file-mount

Client Updated 2026.08.24

Run the following command in DeepSeek Harness:

dsh plugin install acefun29/dsh-file-mount

Paste the following prompt into your AI chat to install this plugin:

Install dsh-file-mount in DeepSeek Harness using the plugin installation flow based on its source repository at https://github.com/acefun29/dsh-file-mount.

About this plugin

In LLM workflows, repeatedly reading files often creates a hidden cost. Logs, configs, code, and documentation can keep filling the context window even when only a small part has changed. dsh-file-mount addresses this by tracking which line ranges of each file have already entered the model context, then avoiding redundant injection on later reads and supplying only the missing or newly changed content.

Its core strength is a file-level context ledger rather than a simple cache. When a file changes on disk, the plugin can compare content line by line and mount only the updated portions, which is especially useful for appended logs. It also recognizes files previously touched by the model and can reuse known context more intelligently. When freshness matters, file_mount_forget lets the model explicitly force a re-read. The bundled dashboard visualizes mounted ranges, freshness, overwrites, savings, search, and sorting, turning token control into something inspectable instead of opaque.

This plugin is best suited for DeepSeek Harness users who repeatedly work with codebases, logs, documentation, configuration files, or long-running conversations. It is especially valuable for people who care about context hygiene, token savings, and observability, and who want a practical way to prevent stale content from crowding out useful context.

Screenshots

Use Cases

  • Avoid re-injecting unchanged lines when reading the same code, log, or document repeatedly.
  • Mount only added or modified lines when files keep changing or growing over time.
  • Inspect mounted file ranges and estimate saved context tokens during long workflows.

Best For

  • Developers who frequently process codebases, logs, and long documents in DeepSeek Harness.
  • Advanced users who care about context pollution, repeated reads, and token savings.
  • Workflow owners who need a visible ledger of mounted files and context efficiency.