FAQ

FAQ

Doesn't prompt caching make this pointless? No, it makes it cheaper. Cached tokens still fill the context window, any change to the tool list misses the cache, and cache reads are discounted, not free. If your agent assembles tools in a varying order, --enable SL007 keeps the cached prefix stable.

Will the model behave differently? At the safe level the model sees the same information, minus duplicates of what the property names and types already say. Any prompt change can shift outputs slightly, so compare on your evals if tool-call accuracy matters, especially with --level annotations.

Is tiktoken accurate for Claude or Gemini? Not exactly, which is why reports say "approximate". Use -t anthropic:<model> for exact Claude counts. Relative savings are stable across tokenizers: within about 2 percentage points in the benchmark.

How much money does this save? Tokens saved per request × requests ÷ 1,000,000 × your model's input price per million tokens. The README FAQ has a worked example.

Does it work offline? Yes, with -t heuristic, or with the tiktoken vocabulary cached via TIKTOKEN_CACHE_DIR.

Is it safe to run on untrusted tool files? Tool files are parsed as data and never executed. --mcp COMMAND does run the command you give it. See SECURITY.md.