# Context Budget

> Audits what is currently consuming the context window — system prompt, tool definitions, conversation history, attached files, retrieved docs — locates the bloat, and cuts or compresses the lowest-value tokens, treating context as a finite budget to be spent deliberately. Use this skill when the user says "context is full", "what's eating my context", "prune this prompt", or "make this cheaper/faster"; when runs feel slow or costly; when too many tools or huge files are loaded; or whenever you need to reclaim room before continuing.

- Skill: `opelpleple/context-budget` (Agent Skill)
- Install (CLI): `npx skillmds@latest add opelpleple/context-budget`
- Raw SKILL.md: https://api.skillmd.com/api/skills/opelpleple/context-budget/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: opelpleple (https://skillmd.com/u/opelpleple)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/opelpleple/context-budget

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# Context Budget

Treat the context window as a finite budget: see where the tokens go, then cut or compress the lowest-value ones first.

## When to use
- The window is near full and you need headroom to keep working.
- Runs feel slow, expensive, or the model seems to be "losing track" (context rot).
- A prompt, tool set, or set of attachments has grown bloated over time.
- The user asks what's consuming context or to optimize token usage.

## When NOT to use
- The context is small and well within budget — don't optimize prematurely.
- Cutting would remove genuinely load-bearing information (then `compact` or `scratchpad` instead — relocate, don't delete).
- The real problem is a missing summary, not bloat — reach for `compact`.

## The method (numbered, concrete — the heart)
1. **Inventory the consumers.** Account for each category and roughly how much it costs: system prompt, tool/function definitions, conversation history, attached/read files, retrieved docs, and prior tool outputs.
2. **Rank by value density.** For each chunk ask: how likely is this to be needed for the *remaining* work, per token it costs? Low-likelihood, high-token chunks are the first targets.
3. **Cut dead weight.** Remove tool definitions you won't use, files read once and finished with, stale retrieved docs, and tool outputs already acted upon.
4. **Compress the rest.** Replace full files with the relevant excerpt; replace verbose history with a `compact` summary; replace big results with their conclusion plus a pointer.
5. **Right-size the toolset.** Fewer, well-chosen tools beat a giant menu — every definition costs tokens *and* dilutes attention. Load tools on demand rather than all upfront.
6. **Push bulk out of the window.** Move reference material to files and pull it back on demand (see `scratchpad`) instead of keeping it resident.
7. **Tighten the system prompt.** Aim for the "right altitude" — specific enough to guide, not a bloated rulebook. Delete redundant, contradictory, or never-triggered instructions.
8. **Re-measure.** Confirm headroom was reclaimed and nothing load-bearing was lost, then continue.

## What good looks like
- You can name the top 3 token consumers and justify each one's keep/cut/compress call.
- The biggest savings came from the highest-token, lowest-value chunks — not from nibbling.
- Nothing essential was deleted; it was relocated to a file or a summary instead.
- The toolset is minimal-sufficient; the system prompt is lean and non-redundant.

## Anti-patterns
- **Trimming the cheap stuff** — shaving a short prompt while a 5,000-line file sits ignored in context.
- **Deleting instead of relocating** — losing information that's needed later instead of offloading it.
- **Tool sprawl** — loading dozens of tool definitions "just in case", taxing every single turn.
- **Pasting whole files** — when one function or section was all that mattered.
- **Optimizing once and forgetting** — budget is a running concern; re-check as the session grows.

## Example (short, vivid)
"Context is full and it's crawling." Quick audit:

| Consumer | Tokens | Verdict |
|---|---|---|
| 3 large files read earlier | ~18k | **Cut** — task moved on; keep paths only |
| 22 tool definitions | ~6k | **Trim** — only 4 used this session |
| Raw stack-trace dumps ×5 | ~4k | **Compress** — keep the one root cause |
| Conversation history | ~12k | **Compact** — summarize to ~2k |
| System prompt | ~1k | Keep |

Result: ~40k reclaimed by attacking the few fat, low-value chunks — the small system prompt was left alone.