# Generated Scene Source Evidence Cross-Scan Design

> Date: 2026-04-20
> Status: Draft
> Parent roadmap:
> - `docs/superpowers/plans/2026-04-20-generated-scene-source-first-runtime-semantics-hardening-plan.md`

## Intent

Execute the first bounded child step of the source-first runtime semantics hardening roadmap:

`scan the original 102 source scenes for high-signal runtime-semantics evidence`

This design does not change analyzer, generator, manifests, or runtime behavior. It only defines how to scan original source-scene evidence so later rule-hardening routes can be derived from source truth rather than from already-generated skills alone.

## Objective

For every scene in the current 102-scene set:

1. locate the original source directory
2. perform a bounded source evidence scan
3. record whether source-side evidence exists for the five anchor gap classes:
   - `invocation_alias_gap`
   - `dictionary_recovery_gap`
   - `parameter_default_semantics_gap`
   - `resolver_to_request_mapping_gap`
   - `runtime_url_semantics_gap`

## Scope

In scope:

1. source directories under:
   - `D:/desk/智能体资料/全量业务场景/一平台场景`
2. current 102-scene mapping from existing materialization / board assets
3. bounded file-content scanning over high-signal files
4. JSON ledger + human-readable report

Out of scope:

1. any code change in `src/`
2. any generated skill change
3. any rematerialization
4. any execution board update
5. any pseudo-production execution

## Required Scan Targets

The scan should prioritize only high-signal evidence sources.

### 1. Invocation alias evidence

Signals:

1. scene name variants
2. menu labels
3. button labels
4. route names
5. report titles
6. user-facing Chinese phrases in HTML / JS

### 2. Dictionary recovery evidence

Signals:

1. `city.js`
2. `dict.js`
3. `enum.js`
4. `options*.js`
5. tree / option arrays with `label`, `value`, `code`, `children`

### 3. Parameter default semantics evidence

Signals:

1. `moment(`
2. `dayjs(`
3. default query parameter assignment
4. implicit month/week/date initialization

### 4. Resolver-to-request mapping evidence

Signals:

1. `$.ajax`
2. `fetch`
3. `contentType`
4. request `data`
5. request body field names
6. mode-specific request payloads

### 5. Runtime URL semantics evidence

Signals:

1. app entry URLs
2. module route URLs
3. API endpoint URLs
4. host runtime / bootstrap page hints

## Scan Strategy

This is not a full source index.

The scan should:

1. use bounded heuristics and targeted filename/content patterns
2. avoid exhaustive deep parsing of every file
3. record evidence flags and representative evidence paths
4. be sufficient to classify scenes for later hardening routes

## Inputs

Primary inputs:

1. `tests/fixtures/generated_scene/scene_skill_102_final_materialization_manifest_2026-04-19.json`
2. `tests/fixtures/generated_scene/scene_execution_board_2026-04-18.json`
3. source root:
   - `D:/desk/智能体资料/全量业务场景/一平台场景`

Anchor validation source:

1. `D:/desk/智能体资料/全量业务场景/一平台场景/台区线损大数据-月_周累计线损率统计分析`

## Output Artifacts

### JSON

- `tests/fixtures/generated_scene/generated_scene_source_evidence_cross_scan_2026-04-20.json`

Each scene record should include:

1. `sceneId`
2. `sceneName`
3. `sourceDir`
4. `evidenceFlags`
5. `evidenceFiles`
6. `riskHints`

### Report

- `docs/superpowers/reports/2026-04-20-generated-scene-source-evidence-cross-scan-report.md`

The report must answer:

1. how many scenes show dictionary evidence
2. how many scenes show default parameter semantics
3. how many scenes show request field aliasing
4. how many scenes show multi-URL semantics
5. which scenes look most similar to `sweep-030-scene`

## Acceptance Criteria

This design is complete when:

1. all 102 scenes are included in the cross-scan
2. the five evidence families are explicit
3. the output JSON structure is defined
4. the scan remains analysis-only

## Stop Statement

Stop after publishing the child design and child plan.

Do not execute the scan inside this design.