Content Audit

> Port provenance: adapted from the pinned upstream source at 984023ddac0d5e27624f2baacde6105e45de375f under MIT; see the repository parity ledger for the exact path and blob.

When this skill is invoked:

Parse the argument:

• No argument → full audit across all systems
• [system-name] → audit that single system only
• --summary → summary table only, no file write

---

Phase 1 — Context Gathering

1. Read design/gdd/systems-index.md for the full list of systems, their

categories, and MVP/priority tier.

1. L0 pre-scan: Before full-reading any GDDs, text search all GDD files for

## Summary sections plus common content-count keywords: `` text search pattern="(## Summary|N enemies|N levels|N items|N abilities|enemy types|item types)" glob="design/gdd/*.md" output_mode="files_with_matches" `` For a single-system audit: skip this step and go straight to full-read. For a full audit: full-read only the GDDs that matched content-count keywords. GDDs with no content-count language (pure mechanics GDDs) are noted as "No auditable content counts" without a full read.

1. Full-read in-scope GDD files (or the single system GDD if a system

name was given).

1. For each GDD, extract explicit content counts or lists. Look for patterns

like:

• "N enemies" / "enemy types:" / list of named enemies
• "N levels" / "N areas" / "N maps" / "N stages"
• "N items" / "N weapons" / "N equipment pieces"
• "N abilities" / "N skills" / "N spells"
• "N dialogue scenes" / "N conversations" / "N cutscenes"
• "N quests" / "N missions" / "N objectives"
• Any explicit enumerated list (bullet list of named content pieces)

1. Build a content inventory table from the extracted data:

| System | Content Type | Specified Count/List | Source GDD | |--------|-------------|---------------------|------------|

Note: If a GDD describes content qualitatively but gives no count, record "Unspecified" and flag it — unspecified counts are a design gap worth noting.

---

Phase 2 — Implementation Scan

For each content type found in Phase 1, scan the relevant directories to count what has been implemented. Use file discovery and text search to locate files.

Levels / Areas / Maps:

• file discovery assets/**/*.tscn, assets/**/*.unity, assets/**/*.umap
• file discovery src/**/*.tscn, src/**/*.unity
• Look for scene files in subdirectories named levels/, areas/, maps/,

worlds/, stages/

• Count unique files that appear to be level/scene definitions (not UI scenes)

Enemies / Characters / NPCs:

• file discovery assets/data/**/enemies/**, assets/data/**/characters/**
• file discovery src/**/enemies/**, src/**/characters/**
• Look for .json, .tres, .asset, .yaml data files defining entity stats
• Look for scene/prefab files in character subdirectories

Items / Equipment / Loot:

• file discovery assets/data/**/items/**, assets/data/**/equipment/**,

assets/data/**/loot/**

• Look for .json, .tres, .asset data files

Abilities / Skills / Spells:

• file discovery assets/data/**/abilities/**, assets/data/**/skills/**,

assets/data/**/spells/**

• Look for .json, .tres, .asset data files

Dialogue / Conversations / Cutscenes:

• file discovery assets/**/*.dialogue, assets/**/*.csv, assets/**/*.ink
• text search for dialogue data files in assets/data/

Quests / Missions:

• file discovery assets/data/**/quests/**, assets/data/**/missions/**
• Look for .json, .yaml definition files

Engine-specific notes (acknowledge in the report):

• Counts are approximations — the skill cannot perfectly parse every engine

format or distinguish editor-only files from shipped content

• Scene files may include both gameplay content and system/UI scenes; the scan

counts all matches and notes this caveat

---

Phase 3 — Gap Report

Produce the gap table:

| System | Content Type | Specified | Found | Gap | Status |
|--------|-------------|-----------|-------|-----|--------|

Status categories:

• COMPLETE — Found ≥ Specified (100%+)
• IN PROGRESS — Found is 50–99% of Specified
• EARLY — Found is 1–49% of Specified
• NOT STARTED — Found is 0

Priority flags: Flag a system as HIGH PRIORITY in the report if:

• Status is NOT STARTED or EARLY, AND
• The system is tagged MVP or Vertical Slice in the systems index, OR
• The systems index shows the system is blocking downstream systems

Summary line:

• Total content items specified (sum of all Specified column values)
• Total content items found (sum of all Found column values)
• Overall gap percentage: (Specified - Found) / Specified * 100

---

Phase 4 — Output

Full audit and single-system modes

Present the gap table and summary to the user. Ask: "May I write the full report to docs/content-audit-[YYYY-MM-DD].md?"

If yes, write the file:

# Content Audit — [Date]

## Summary
- **Total specified**: [N] content items across [M] systems
- **Total found**: [N]
- **Gap**: [N] items ([X%] unimplemented)
- **Scope**: [Full audit | System: name]

> Note: Counts are approximations based on file scanning.
> The audit cannot distinguish shipped content from editor/test assets.
> Manual verification is recommended for any HIGH PRIORITY gaps.

## Gap Table

| System | Content Type | Specified | Found | Gap | Status |
|--------|-------------|-----------|-------|-----|--------|

## HIGH PRIORITY Gaps

[List systems flagged HIGH PRIORITY with rationale]

## Per-System Breakdown

### [System Name]
- **GDD**: `design/gdd/[file].md`
- **Content types audited**: [list]
- **Notes**: [any caveats about scan accuracy for this system]

## Recommendation

Focus implementation effort on:
1. [Highest-gap HIGH PRIORITY system]
2. [Second system]
3. [Third system]

## Unspecified Content Counts

The following GDDs describe content without giving explicit counts.
Consider adding counts to improve auditability:
[List of GDDs and content types with "Unspecified"]

After writing the report, ask:

> "Would you like to create backlog stories for any of the content gaps?"

If yes: for each system the user selects, suggest a story title and point them to $ai-game-studio:create-stories [epic-slug] or $ai-game-studio:quick-design depending on the size of the gap.

--summary mode

Print the Gap Table and Summary directly to conversation. Do not write a file. End with: "Run $ai-game-studio:content-audit without --summary to write the full report."

---

Phase 5 — Next Steps

After the audit, recommend the highest-value follow-up actions:

• If any system is NOT STARTED and MVP-tagged → "Run $ai-game-studio:design-system [name] to

add missing content counts to the GDD before implementation begins."

• If total gap is >50% → "Run $ai-game-studio:sprint-plan to allocate content work across upcoming sprints."
• If backlog stories are needed → "Run $ai-game-studio:create-stories [epic-slug] for each HIGH PRIORITY gap."
• If --summary was used → "Run $ai-game-studio:content-audit (no flag) to write the full report to docs/."

Verdict: COMPLETE — content audit finished.

Codex portability

Use the search, file-editing, shell, user-input, and subagent capabilities available in the active Codex surface. Use PowerShell syntax on Windows and POSIX syntax on macOS/Linux; do not require a Unix compatibility layer on Windows. Inherit the active model and permission mode, and do not weaken approval or sandbox boundaries.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: frabcd
• Source: frabcd/codex-ai-game-studio
• License: MIT
• Homepage: https://frabcd.github.io/codex-ai-game-studio/

Install and usage instructions live in the source repository linked above.