Context Budget
SkillAI & modelsTeaches your agent a context claude skill for spending tokens wisely in long coding sessions.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Context Budget skill
About this skill
Use when a coding session is burning context fast, output is drowning in noise, the model keeps forgetting earlier decisions, or the user asks to reduce tokens, stop the verbose narration, work in a huge repo, or make a long session survive. Covers what to read, what to summarize, what to write to d
What this skill tells your AI
The instructions your AI receives, as published by onewave-ai/claude-skills in context-budget/SKILL.md and read by ahel’s review.
Context is the scarcest resource in a long session. It gets spent on three things: files you read, output you generate, and narration nobody asked for. Only the first one is usually worth it.
Core Behavior
Treat the context window like a budget with a balance. Before any expensive action — reading a big file, running a chatty command, dumping a directory tree — ask what the cheapest way to get the same answer is.
Spend Rules
Read narrowly. sed -n '120,190p' file.ts beats reading a 2,000-line file to see one function. Grep for the symbol, then read the 40 lines around it. Read a whole file only when you are about to restructure it.
Search before reading. grep -rn "symbolName" --include="*.ts" costs a few hundred tokens and tells you which of forty files matters.
Silence the noisy commands. Pipe installs, builds, and test runs through a filter instead of dumping them whole:
npm test 2>&1 | tail -30
npm run build 2>&1 | grep -E "error|Error|warning" | head -20
npm install --silent 2>&1 | tail -5
git diff --stat # not git diff, unless you need the hunks
A passing test suite needs one line of proof, not 400.
Write instead of remembering. Anything that must survive — a plan, a decision, a list of files to touch — goes in a file on disk. Files are re-readable at a cost you choose; context is not.
Do not re-read what you just wrote. If an edit succeeded, it succeeded. Re-reading to "verify" is pure spend.
Cut the narration. No preamble, no recap of what was just shown, no bulleted summary of a diff the user can see. Say what changed and what is next, in a line or two.
Where the Budget Actually Goes
When a session bloats, it is almost always one of these:
| Leak | Fix |
|---|---|
| Whole-file reads for one function | grep, then a line-ranged read |
Full npm install / build logs | | tail -n or grep for errors |
Directory listings of node_modules, dist, .next | prune them in the find/ls |
| Re-reading files after editing | trust the edit result |
| Long explanations of finished work | one line |
| Pasting a file back to show a small change | show the diff hunk only |
| Repeating the plan every turn | plan lives in a file |
Compaction Points
When roughly two-thirds of the window is gone, stop adding and start consolidating:
- Write the current state to a plan or handoff file on disk.
- State the single next action.
- Tell the user a fresh session will be faster and more accurate than continuing.
A fresh session that reads a good plan file outperforms a stuffed session every time. Do not treat starting over as failure — it is the intended move.
Large Repos
- Map before you dig: directory names and entry points first, implementation later.
- Follow imports from the entry point rather than crawling folders alphabetically.
- One subsystem at a time. Finish it, write down what you learned, move on.
- Generated code, lockfiles, and snapshots are never worth reading. Exclude them by default.
What Not to Cut
Economy has a floor. Never skip:
- Reading the actual code before changing it.
- The error output when something failed — that is the one long dump worth having.
- The user's own requirements, quoted.
Being cheap about the wrong thing produces confident, wrong work. The goal is fewer tokens, not less evidence.
Signals
- GitHub stars
- 306
- Forks
- 52
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packages
Automated review, not a security audit. Ruleset v1+k2.
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context-budget-onewave-ai- Source
- github.com/onewave-ai/claude-skills