DeepSeek Harness Plugin

WODE25500/dsh-token-skills

Stars ★ 2 Category Skills Added 2026-09-01

Cut token cost in 4 layers without cutting model intelligence: handoff, rtk, headroom, caveman token-saving skills — each also available as a standalone installable plugin.

Install

# from GitHub (first run asks for allowBuilds approval — follow the hint, retry)

dsh plugin --profile web add github:WODE25500/dsh-token-skills

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

Cut token cost in 4 layers — without cutting model intelligence.

A DeepSeek Harness preset of four complementary token-saving skills. Each one attacks a different stage of the token pipeline, so they stack:

handoff the context → prune the input → compact the context → terse the output

Stop paying twice for tokens you already have.

flowchart LR
  A[Tokenizer] --> B[① Handoff<br>session]
  B --> C[② RTK<br>input]
  C --> D[③ Headroom<br>context]
  D --> E[④ Caveman<br>output]
  E --> F[<b>fewer tokens</b>]

Why: every token is money. A long agent session re-sends context it already paid for — past transcripts, padded logs, verbose replies. These four skills stop that leak at each stage.


The four layers

# Skill Layer What it saves Backs off to
① handoff Session stop re-reading/rebuilding context between sessions context-auto-handoff
② rtk Input drop redundant/repeated tokens before they enter the model RTK (Rust Token Killer)
③ headroom Context compress the live context so the prompt stays small WanYanTianDe/dsh-headroom
④ caveman Output terse prose — fewer tokens on the way out skill-caveman

Each layer is a thin dsh skill (skills/<layer>/SKILL.md). Where a real engine already exists, the skill wires to it instead of re-implementing compression — you get the strategy and the engine, for free.


Standalone repos

Each layer is also its own installable plugin, so you can add just the one you want:

Skill Repo
handoff WODE25500/dsh-token-handoff
rtk WODE25500/dsh-token-rtk
headroom WODE25500/dsh-token-headroom
caveman WODE25500/dsh-token-caveman
# install just one
dsh plugin --profile web add dsh-token-handoff

When to use which

  • Handoff — the highest-leverage, cheapest habit: write a HANDOFF.md note at session end so the next one starts warm. Use it on every multi-session project.
  • RTK — per request, before you paste a big file/log/repo listing that's mostly noise.
  • Headroom — continuous, for long-lived agents: compact before the window fills, not at the cliff edge.
  • Caveman — every reply: it costs nothing and compounds. It changes style, never substance.

They stack to a single habit, not a heavy setup:

before: [past session verbatim] + [entire repo dump] + [fat context] + [verbose response]
after:  HANDOFF note      → pruned diff      → compacted headroom  → terse reply

Install

dsh plugin --profile web add dsh-token-skills

Or clone it and drop the skills into ~/.dsh/skills/:

git clone https://github.com/WODE25500/dsh-token-skills

Each skill is also invocable directly — handoff, rtk, headroom, caveman.


Validation

npm test   # runs scripts/check-skills.mjs — asserts every bundled skill's frontmatter

License

MIT

Content from the project README on GitHub ↗

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