Delegate
Skill chinayin/gox-claude-plugins/plugins/token-thrift/skills/delegate
Token-saving subagent routing. Use when facing token-heavy, read-heavy, conclusion-only work (reading Lark/Feishu in full or writing to it, wide code searches, log/long-document analysis) to decide whether to offload the work to a cheaper-model subagent and which tier to use.From its SKILL.md
npx -y skills add chinayin/gox-claude-plugins --skill delegateAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
1.8 KB, 378 tokens by cl100k_base, as published. Nobody here has run it
Token-saving three-tier split
The main agent (Opus) does only orchestration and decisions with the user. Offload token-heavy work; keep raw material out of the main context.
Which tier
| Kind of work | Dispatch to | Model | Why |
|---|---|---|---|
| Read / compare / verify / search (conclusion only) | cheap-reader | Haiku | Cheapest ($1/$5); raw material is read once and discarded |
| Correctness-sensitive writes (Lark/Feishu XML/blocks, reliable persistence) | careful-writer | Sonnet | Write errors are costly; Sonnet is only 40–60% of Opus |
| Orchestration / decisions | main agent | Opus | Keep the main context lean |
A read that needs subtle judgment may be promoted to Sonnet; a purely mechanical append may drop to Haiku.
When it's worth offloading
Rule of thumb: offload when the throwaway material the subagent must process is ≳ 3,000 tokens. Because:
- Skill loading (e.g.
lark-*SKILL + references, often tens of thousands of tokens) moves from Opus pricing to the cheaper model's pricing. - Raw material stays out of the main context, avoiding it being re-billed on every subsequent turn (the biggest lever).
If the task is tiny, or the main thread will need the raw material again, keep it inline instead.
How to dispatch
Use the Task/Agent tool with subagent_type set to cheap-reader or careful-writer. Have it return only a compact conclusion; if the result is large, have it write a scratchpad file and return the path. Keep the Opus main context lean.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.