Hallx – Hallucination risk scoring for LLM outputs
Yet another hallucination checker when Guardrails and LMQL already cover this.
Config-driven CLI tool that compresses command output before it reaches an LLM context
Cuts cargo test output from 61 lines to 1 — saves 60-90% of wasted LLM tokens.
Developers using Claude Code or similar AI coding assistants
tokf is a Rust CLI that intercepts command output and compresses it using TOML-defined filters. You can strip passing tests, collapse repetitive errors, trim stack traces, etc.
The tricky part was making it work with build orchestrators. Hooking `just test` doesn't help if the noisy output comes from the `cargo test` that just runs internally. I ended up solving this three different ways depending on the tool:
- make/just: use their --shell flag to route execution through tokf - git hooks / other tools: prepend a shim directory to PATH
Wrote up the full rabbit hole: https://pecan.si/posts/getting-into-make-just-and-hooks/
Built in Rust, ~1,800 daily executions in my workflow. Filters are TOML with a Lua escape hatch. Open source: https://tokf.net
Yet another hallucination checker when Guardrails and LMQL already cover this.
Tree-sitter interface extraction cuts token usage by 6x, but chat context window optimization is becoming table stakes.
Entropy-based context compression beats naive token stuffing, but the category is crowded.
Git metaphor for agent memory is clever; execution and adoption remain unproven.
Deterministic FSM guards LLM outputs to prevent hallucination spirals in .NET.
Typed, hookable agent loop in Rust when LangChain dominates Python.