---
name: domain-case-loop
description: Use this skill when a user wants to iteratively refine one NDC_1C domain case through a multi-agent loop: automated baseline capture, JSON analysis, minimal domain patch, rerun, and before/after verdict.
---

# Domain case loop

This skill packages the standard workflow for iterating on one concrete domain case in NDC_1C.

## Use this skill when

- the user wants to improve one domain question end-to-end;
- the answer exists but is noisy, heuristic, partial, or business-useless;
- the route is wrong even if the wording looks better;
- there is a gap between exact compute intent and actual fallback output;
- there are follow-up / continuation bugs that corrupt business context.

## Do not use this skill when

- the user is asking for a broad architecture rewrite;
- there is no concrete domain case or no reproducible input;
- the task is only prose editing with no technical/domain component;
- the task is a generic repo cleanup unrelated to domain capability behavior.

## Repo-specific runtime map

Read `references/repo_runtime_map.md` before the first real cycle.

Use these repo-native capture paths:
- automated capture: `python scripts/domain_case_loop.py run-case ...`
- import existing technical export: `python scripts/domain_case_loop.py import-export ...`

## Workflow

### Step 1 - Normalize the case

Create `artifacts/domain_runs/<case_id>/case_brief.md` with:
- domain name
- raw user question
- expected business meaning
- expected exact capability
- expected result mode
- known constraints
- acceptance criteria draft

Use `references/case_brief_template.md`.

### Step 2 - Capture baseline

Preferred path:
- run `python scripts/domain_case_loop.py run-case ...`

Fallback path:
- if the user already has a copied technical export markdown, run `python scripts/domain_case_loop.py import-export ...`

Required artifacts:
- `baseline_output.md`
- `baseline_debug.json`
- `baseline_turn.json`

### Step 3 - Analyst verdict

Spawn `domain_analyst` and provide:
- `case_brief.md`
- `baseline_turn.json`
- `baseline_output.md`
- `baseline_debug.json`
- optional relevant code excerpts or file paths

Require a full verdict using `references/verdict_template.md`.

### Step 4 - Domain patch

Spawn `domain_coder` with:
- the case brief
- the analyst verdict
- baseline artifacts

Require:
- a minimal patch
- zero architecture drift
- rerun after changes

### Step 5 - Rerun

Capture:
- `rerun_output.md`
- `rerun_debug.json`
- `rerun_turn.json`
- `patch_summary.md`

### Step 6 - Before/after analysis

Spawn `domain_analyst` again for:
- before/after comparison
- final status recommendation
- quality score from 0 to 100

### Step 7 - Final status

Write `final_status.md` with one of:
- accepted
- partial
- blocked
- needs_exact_capability

Accepted requires:
- quality score >= 80
- no unresolved P0 defects
- no silent heuristic masking

## Hard rules

- Do not count heuristic candidates as confirmed business answers.
- If exact data should exist in 1C/MCP, prefer exact route work over prompt cosmetics.
- If exact data does not exist yet in the reachable contour, return a technical insufficiency with a crisp blocker.
- Never fabricate 1C data.
- Keep domain fixes minimal and localized.
- Preserve successful baseline scenarios.
- Treat follow-up continuity as a state-machine problem, not a wording problem.

## Domain-specific framing

For this repository:
- architecture must remain unchanged;
- 1C/MCP is the primary source of truth;
- analyst output must be detailed and business-readable;
- answers should be suitable for product hardening, not just debugging notes;
- machine-readable turn artifacts are first-class inputs for analysis.

## Recommended artifact set

Use the artifact layout from `references/artifact_layout.md`.