Map the boundaries and define types

Find every place prose crosses into code.

First time here? Paste the Context Pack first so the AI understands your project - open it from the header above.

Prompt Capsule

Inventory every model-to-system boundary in my pipeline: tool-call arguments, extraction outputs, classification results, generation outputs consumed by code, and inter-agent messages. For each, define the output type as a schema: precise field types, enums for closed sets, optionality that reflects reality, and field descriptions (they double as generation guidance). Flag the boundaries currently parsed by regex or string-splitting - these are the incident factories and get migrated first. Deliver the boundary inventory with schemas drafted for the top 5.

Paste into EmergentFull Build: complete implementation prompt with explicit requirements

Quick is short. Full Build is recommended for most steps. Strict forces real logic when the AI keeps faking output.

Actual change check

Expected after this step

A boundary inventory with schemas for the riskiest five.

Should NOT happen

An existing feature broke
A button only logs to console
Data disappears after refresh
Errors fail silently with no visible state

This is what should exist before you continue. If reality does not match, do not move on.

Your notes for this step

Track what changed, failed, or needs follow-up. Notes export with the flow.

Pass the Verify Gate to complete this step

Verify before continuing

Do not move on until every check is true. The complete button stays locked until then.

All boundaries listed with current parsing methodRegex boundaries flagged for prioritySchemas drafted with enums and descriptions

Do not continue if…

! Regex scraping of markdown that breaks on every format drift
! Schemas that exist but are not enforced at runtime
! Unbounded repair loops burning tokens on unfixable output
! Silent fallbacks that fabricate data downstream systems trust

If the AI messes this up

Use this when:

- it only made visual forms or placeholder UI
- buttons do nothing or only log to console
- data is not persisted - state disappears on refresh
- something that worked before is now broken

Use this when the AI fakes progress or breaks the feature. It forces a real fix.

The inventory missed boundaries. Grep the codebase for json.loads, regex on model output, and .split( near LLM calls - each hit is a boundary someone forgot.