id-token-nicer
https://github.com/thejens/id-token-nicer- Category
- Developer Tools
- Rank
- No. 2138Tools index
Previous survey · No. 2114 ·
- Pricing
- Open Source
- Type
- TOOL
- Builder
- thejens
- GitHub
- 1 stars
- Date
About
Encode UUIDs and integers as word sequences that LLM agents can read and reproduce reliably.
What it does
This toolkit puts a safer translation layer around identifiers used in model conversations. It can create reversible phrases, scramble predictable integer patterns, detect malformed references with checksums, or temporarily replace UUIDs with compact placeholders and restore the originals after a model responds.
Why it's ranked here
The design addresses several distinct identifier failures with practical mechanisms instead of one cosmetic encoding. Checksums flag corruption, substitution keeps raw UUIDs outside model context, and reversible mixing obscures sequences. The case is weakened by documentation claims about token behavior that exceed what the word-list generator guarantees.
What's good
It supports UUIDs, variable-length integers, fixed-width integers, and arbitrary bytes through Rust and Python. Decoding hashes words directly to slots, so work scales with phrase length. Five vocabulary sizes expose a clear phrase-length tradeoff. Bloom filters reject many typos early, while checksums provide a separate validation layer.
Tradeoffs
Python installation builds from source and requires both Rust and Maturin. Phrase encoding does not stop a model from reusing a valid identifier in the wrong context, so applications still need authorization and context checks. The token-list generator permits dictionary and generated fallback words, despite broader documentation claims that every word is one token across named model families.
How to use it well
Use it around agent tools, prompts, and responses that repeatedly carry UUIDs or integer record keys. Prefer placeholder substitution when exact UUID preservation matters most, and fixed-width mixing when sequential identifiers expose patterns. Treat it as an identifier transport and validation layer, not access control, object authorization, or semantic reference checking.
Technical notes+
Cargo.toml defines a Rust 2024 crate producing cdylib and rlib artifacts plus the id-tokenizer binary; pyproject.toml builds the CPython package with Maturin and PyO3. src/codec.rs packs payload and checksum bits into vocabulary slots, derives slots with xxh64, validates membership through src/bloom.rs, and reverses Feistel transforms from src/mix.rs. src/main.rs provides encode/decode commands, stdin processing, type detection, five vocabulary sizes, and memorable or token styles. src/python.rs exposes Codec plus UUID, integer, fixed-width, byte, counting, and mixing functions. python/id_tokenizer/_registry.py implements in-memory and JSON-backed placeholder registries, while python/id_tokenizer/__init__.py exports substitution support. tools/gen_tokenlist.py uses tiered tokenizer coverage and fallback words, which does not establish universal single-token coverage for every generated list entry.
Observed
- License
- MIT, declared in pyproject.toml
- Primary implementation
- Rust core with CPython bindings implemented through PyO3
- Interfaces
- Rust library, Python library, and id-tokenizer command-line interface
- Python packaging
- Maturin build backend; Python 3.9 or newer; no declared runtime Python dependencies
- Source installation
- README requires Rust 1.80 or newer and Maturin for Python builds; Cargo installs the CLI from the repository
- Crate outputs
- Cargo configuration produces cdylib and rlib library artifacts plus a binary
Read from README.md, Cargo.toml, pyproject.toml, src/lib.rs, src/main.rs, src/mix.rs, src/bloom.rs, src/codec.rs, src/python.rs, src/checksum.rs, tools/gen_wordlist.py, tools/gen_tokenlist.py, python/id_tokenizer/_cli.py, python/id_tokenizer/__init__.py, python/id_tokenizer/_registry.py.
What it can do
Encode UUIDs as word sequences
UUID → Human-readable word sequence
Encode integers as word sequences
Integer → Human-readable word sequence
Decode word sequences back to UUIDs
Word sequence → UUID
Decode word sequences back to integers
Word sequence → Integer
Generate LLM-friendly token representations
UUID or integer → Token sequence optimized for LLM processing
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Tech Stack
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