Input redundancy pruning for DeepSeek Harness — drop repeated/redundant tokens before they reach the model (layer ②).
Install
# from GitHub (first run asks for allowBuilds approval — follow the hint, retry)
dsh plugin --profile web add github:WODE25500/dsh-token-rtk
Any plugin you install runs third-party code with your own permissions — it can read your files, use your credentials, and reach the network, and tool approvals don’t sandbox it. GitHub-sourced plugins also run build scripts at install time — pnpm blocks those until you allow them, so an install can stop with ERR_PNPM_GIT_DEP_PREPARE_NOT_ALLOWED or ERR_PNPM_IGNORED_BUILDS; dsh prints the exact key to add under allowBuilds in your profile’s pnpm-workspace.yaml, and the install works on the next run. Allowing a build is a trust decision: only install sources you trust, and pin a commit (github:owner/repo#sha).
README
Input redundancy pruning — drop repeated/redundant tokens before they reach the model. — a DeepSeek Harness (dsh) skill, layer rtk of a four-layer token-saving family.
Trim verbose logs, duplicated warnings, whole-file pastes, and noise around the real signal so you pay for the signal you need, not the boilerplate around it. (RTK = Rust Token Killer strategy.)
Family: dsh-token-skills groups all four layers — handoff, rtk, headroom, caveman.
Install
dsh plugin --profile web add dsh-token-rtk
Then invoke the skill: dsh-token-rtk.
Upstream
Based on / referencing https://mintlify.wiki/rtk-ai/rtk/faq. This repo is the DSH adaptation — a thin skill, not a re-implementation of the engine.
License
MIT
Links
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