Individual skill
language-spec-author
Turn a rough idea for a language into a complete, implementable specification — a DSL, query, config/data, template, or protocol language — by interviewing the author dimension by dimension until another developer could build a conforming implementation from the document alone. It grills for the decisions authors skip: lexical rules (whitespace, case, comments, literals), grammar with precedence and ambiguity resolution, a semantic/type model, validation rules with counter-examples, execution algorithms and the error model, the output/serialization format, and RFC 2119 conformance. The completeness bar and formal notation (lexical vs syntactic grammar, function-style algorithms) are distilled from the GraphQL specification. Trigger on "spec out my language", "design a DSL / query language", "write a language or grammar spec", "formalize this syntax", or when someone has a language idea that needs to become an implementable spec — even if they only say "spec" or "grammar".
skills/.experimental/language-spec-author/SKILL.md
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- Observed behavior
- Local scripts
- Last checked
- Nov 5, 2026
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- Repository stars (not skill ratings)
- 221
- Repository last updated
- Aug 15, 2026
- License
- MIT
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- engineering Derived category
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SKILL.mdcore · 9,879 bytesSKILL.mdcore · 9,879 bytesassets/templates/spec-template.mddoc · 5,237 bytesgotchas.mddoc · 2,099 bytesmetadata.jsonasset · 970 bytesreferences/formal-notation.mddoc · 7,149 bytesreferences/interview-playbook.mddoc · 7,416 bytesreferences/spec-anatomy.mddoc · 10,370 bytesscripts/check-spec.shruns · 5,769 bytesscripts/new-spec.shruns · 3,415 bytes
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# Author an Implementable Language Specification
Take an author from a rough language idea to a specification precise enough that a
developer with **zero access to the author** can build a conforming implementation from
the document alone. The output is a spec in the mold of the
[GraphQL specification](https://spec.graphql.org/draft/) — grammar, semantics, validation,
execution, and conformance — that other devs can implement and interoperate against.
The hard part of a language spec is not prose; it is eliminating the ambiguities the
author does not know they are leaving. Two implementers reading a vague sentence produce
two incompatible languages. So this skill's method is **grilling**: ask one sharp
question at a time, recommend a default, and refuse to write down any answer that fails
the stranger / edge-case / two-implementers tests. It bundles a scaffold script, a
completeness linter, and reference docs for the anatomy, the formal notation, and the
interview itself.