Toolshrink — Development skill for Claude Code

toolshrink

**Cut large agent tool output by what it means, not by where it was cut.**

I use Claude Code every day, and I always wanted to intervene in how it manages context. In the early days you could edit the session JSONL directly. Then that door closed.

When DeepSeek open-sourced Harness, where everything is a plugin, I looked inside. Tool output there is cut by size: keep the head, keep the tail, drop the middle. I read Codex and pi, and they do the same. None of them look at what the text contains.

That fails in a predictable way. Your test suite prints 5,000 passing lines and 3 failures in the middle. A size cut keeps the passes and throws away the failures. The model reads it, believes the run, and answers wrong.

So I built the shrinker I always wished Claude Code had. It reads the output first, recognizes its shape, and keeps the part that carries the information:

input: a vitest run, 31,958 chars, 805 lines, budget 2,000 chars

head+tail cut:   1,904 chars   the model learns: the summary
toolshrink:        255 chars   the model learns: which test failed,
                               why, at which line, and the summary

Everything removed is counted in a marker the model can read, and the complete original is saved to disk with a locator. Nothing is lost silently.

The cuts

Each cut recognizes one shape of text. The first one that recognizes the input runs. When none does, the size fallback runs, so the result always fits the budget.

Cut	Recognizes	Keeps	Drops
diff	git diff, patches	changed lines, file and hunk headers, 1 context line each side	unchanged context
json	one JSON value	the structure, 3 samples per long array, 5 keys per wide object, counts	repeated records
tests	vitest, jest, pytest, cargo test, go test	failures with their explanation, the summary	passing tests
build	tsc, cargo, gcc, webpack, esbuild	errors and warnings with their code frame,