05. Iteration

Building a reliable DSL pipeline is rarely one-shot. The typical workflow is a short loop: run → observe → tighten → repeat.

The iteration loop

1. Write grammar + prompt
2. Run against a sample input
3. Inspect the canonical DSL the LLM produced
4. If the grammar rejects it — tighten the prompt or relax the token
5. If the grammar accepts it but the data is wrong — tighten the token
6. Repeat until the full sample set passes

Tool: Slangify Playground

Playground Link

https://slangify.org/playground lets you paste a grammar and type DSL lines directly to test token rules without any LLM round-trip. Fast feedback for grammar iteration — no local install required.

You can Share a url to the playground to distribute the DSL model to colleagues - the DSL selector limits the view to input and made panels only for less technical team members.

Workflow:

• Paste Slangify::Tutorial::Grammar into the grammar panel

• Paste Slangify::Tutorial::Action into the action panel

• Type a canonical DSL line into the input panel

• The playground shows the parse tree and named captures immediately

• Tweak a token, re-paste, re-run — tight loop with no Raku install needed

• Share a permalink to your grammar with collaborators

Tool: Grammar::Editor

The Grammar::Editor module is a convenient tool for those that prefer a Terminal User Interface (TUI) environment.

Workflow:

• Paste both Slangify::Tutorial::Grammar and Slangify::Tutorial::Actions

• Run against a canonical DSL line to verify the Booking object is populated correctly

Other Tools

For general Raku programming, a selection of IDE and editor tooling can be found at https://raku.org/tools.

Logging the canonical DSL

Always log the intermediate DSL string so you can see exactly what the LLM produced before the grammar runs:

sub parse-booking(Str $text --> Str) is export {
    my $canonical = normalize-text($text);
    note "canonical: $canonical";          # ← add during development
    my $match = Slangify::Tutorial::Grammar.parse(
        $canonical,
        :actions(Slangify::Tutorial::Actions.new)
    );
    die "Parse failed on: $canonical" unless $match;
    $match.made.raku
}

The note line writes to STDERR so it doesn't pollute the JSON output. Remove it once the grammar is stable.

Common iteration scenarios

LLM uses the wrong field name

The LLM outputs guests 4 instead of party 4. Fix: add an alias example to the prompt, or rename the token to match natural LLM output.

LLM adds extra fields

The LLM outputs name "Jane" party 4 time 19:30 restaurant "Bistro Verde" date tomorrow notes "window seat". The grammar rejects it because notes is unknown. Fix: either add a notes token to the grammar, or add a rule to the prompt: Output ONLY the five specified fields.

LLM drops optional fields

The LLM omits date when it is not mentioned. Fix: make the token optional in TOP with ? and handle the missing case in Booking.

Token too strict

Your token time { <[0..2]>\d ':' <[0..5]>\d } rejects 9:00 (single digit hour). Fix: token time { \d\d? ':' <[0..5]>\d }.