Kalebtec
Context Specification Language
maio de 2026
A Rust reference toolchain and evaluation harness for structured, machine-addressable specification documents — a rigorous alternative to unstructured Markdown for feeding AI agents their context. Implements a full parse, validate, normalize, serialize, and evaluate pipeline with repository-aware file-reference checking.
Caso de estudo
Reto
AI agents are only as good as the context they receive, yet most context is unstructured Markdown that is hard to validate, address, or evaluate. Kalebtec wanted a rigorous, machine-addressable format instead.
Enfoque técnico
Built a Rust reference toolchain: a parser and writer, a validator and normalizer, a serializer, and an evaluation harness — with repository-aware checking of file references so a specification cannot silently point at something that no longer exists.
Decisións de IA e infraestrutura
Rust for correctness and speed; a full parse-validate-normalize-serialize-evaluate pipeline so specifications are structured data, not prose; and an eval harness with TOML/JSON reporting so context quality can be measured, not guessed.
Resultados
A working toolchain that turns agent context into structured, checkable documents with deterministic tooling around them.
Impacto no negocio
This is Kalebtec's own IP and a signal of how we think about applied AI: reliability and evaluation over prompt-and-pray.
Overview
Context Specification Language (CSL) is a Kalebtec toolchain for describing AI-agent context as structured, machine-addressable documents rather than unstructured Markdown, with tooling to validate, normalize, and evaluate it.
What We Built
Reference Toolchain
A Rust implementation covering parsing, validation, normalization, and serialization, plus a CLI and repository-aware file-reference checking so specifications stay honest as a codebase evolves.
Evaluation Harness
A refinement and evaluation harness with TOML/JSON reporting, so the quality of a specification — and the context it produces for an agent — can be measured and improved deterministically.
Delivery Focus
- Machine-addressable specifications instead of unstructured prose
- Correctness-first Rust implementation with property-based testing
- Evaluation as a first-class part of the toolchain