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name: token-conservation description: | Minimize token usage through conservative prompting, work delegation, and quota tracking.

Triggers: token usage, quota, token limits, prompt size, token conservation, usage tracking, delegation, context compression, token budget

Use when: session starts (mandatory), prompt sizes spike, tool calls increase, before long-running analyses or massive context loads

DO NOT use when: context-optimization already handles the scenario. DO NOT use when: simple queries with minimal context.

Use this skill at the START of every session. This is MANDATORY for quota management. location: plugin token_budget: 300 progressive_loading: true dependencies: hub: [] modules: []

Token Conservation Workflow

When to Use

• Run at the start of every session and whenever prompt sizes or tool calls begin to spike.
• Mandatory before launching long-running analyses, wide diffs, or massive context loads.

Required TodoWrite Items

1. token-conservation:quota-check
2. token-conservation:context-plan
3. token-conservation:delegation-check
4. token-conservation:compression-review
5. token-conservation:logging

Step 1 – Quota Check (quota-check)

• Record current session duration and weekly usage (from /status or notebook). Note the 5-hour rolling cap + weekly cap highlighted in the Claude community notice.
• Capture remaining budget and set a max token target for this task.

Step 2 – Context Plan (context-plan)

• Decide exactly which files/snippets to expose. Prefer rg/sed -n slices instead of whole files.
• Convert prose instructions into bullet lists before prompting so only essential info hits the model.

Step 3 – Delegation Check (delegation-check)

• Evaluate whether compute-intensive tasks can go to Qwen MCP or other external tooling (use qwen-delegation skill if needed).
• For local work, favor deterministic scripts (formatters, analyzers) instead of LLM reasoning when possible.

Step 4 – Compression Review (compression-review)

• Summarize prior steps/results before adding new context. Remove redundant history, collapse logs, and avoid reposting identical code.
• Use prompt caching ideas: reference prior outputs instead of restating them when the model has already processed the information (cite snippet IDs).
• Decide whether the current thread should be compacted:
  • If the active workflow is finished and earlier context will not be reused, instruct the user to run /new
  • If progress requires the existing thread but the window is bloated, prompt them to run /compact before continuing

Step 5 – Logging (logging)

Document the conservation tactics that were applied and note the remaining token budget. If the budget is low, explicitly warn the user and propose secondary plans. Record any recommendations made regarding the use of /new or /compact, or justify why neither was necessary, to inform future context-handling decisions.

Output Expectations

• A short explanation of token-saving steps, delegated tasks, and remaining runway.
• Concrete next-action list that keeps the conversation lean (e.g.):
  • "next turn: provide only failing test output lines 40-60"
• Explicit reminder about /new or /compact whenever you determine it would save tokens (otherwise state that no reset/compaction is needed yet).