content-audit▌
Donchitos/Claude-Code-Game-Studios · updated Apr 16, 2026
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### Content Audit
- ›description: "Audit GDD-specified content counts against implemented content. Identifies what's planned vs built."
- ›argument-hint: "[system-name | --summary | (no arg = full audit)]"
- ›allowed-tools: Read, Glob, Grep, Write
| name | content-audit |
| description | "Audit GDD-specified content counts against implemented content. Identifies what's planned vs built." |
| argument-hint | "[system-name | --summary | (no arg = full audit)]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Write |
| agent | producer |
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
-
Read
design/gdd/systems-index.mdfor the full list of systems, their categories, and MVP/priority tier. -
L0 pre-scan: Before full-reading any GDDs, Grep all GDD files for
## Summarysections plus common content-count keywords:Grep 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.
-
Full-read in-scope GDD files (or the single system GDD if a system name was given).
-
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)
-
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 Glob and Grep to locate files.
Levels / Areas / Maps:
- Glob
assets/**/*.tscn,assets/**/*.unity,assets/**/*.umap - Glob
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:
- Glob
assets/data/**/enemies/**,assets/data/**/characters/** - Glob
src/**/enemies/**,src/**/characters/** - Look for
.json,.tres,.asset,.yamldata files defining entity stats - Look for scene/prefab files in character subdirectories
Items / Equipment / Loot:
- Glob
assets/data/**/items/**,assets/data/**/equipment/**,assets/data/**/loot/** - Look for
.json,.tres,.assetdata files
Abilities / Skills / Spells:
- Glob
assets/data/**/abilities/**,assets/data/**/skills/**,assets/data/**/spells/** - Look for
.json,.tres,.assetdata files
Dialogue / Conversations / Cutscenes:
- Glob
assets/**/*.dialogue,assets/**/*.csv,assets/**/*.ink - Grep for dialogue data files in
assets/data/
Quests / Missions:
- Glob
assets/data/**/quests/**,assets/data/**/missions/** - Look for
.json,.yamldefinition 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 SpecifiedEARLY— Found is 1–49% of SpecifiedNOT STARTED— Found is 0
Priority flags:
Flag a system as HIGH PRIORITY in the report if:
- Status is
NOT STARTEDorEARLY, 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 /create-stories [epic-slug] or /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 /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 STARTEDand MVP-tagged → "Run/design-system [name]to add missing content counts to the GDD before implementation begins." - If total gap is >50% → "Run
/sprint-planto allocate content work across upcoming sprints." - If backlog stories are needed → "Run
/create-stories [epic-slug]for each HIGH PRIORITY gap." - If
--summarywas used → "Run/content-audit(no flag) to write the full report todocs/."
Verdict: COMPLETE — content audit finished.
How to use content-audit on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add content-audit
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches content-audit from GitHub repository Donchitos/Claude-Code-Game-Studios and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate content-audit. Access the skill through slash commands (e.g., /content-audit) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★68 reviews- ★★★★★Ava Sharma· Dec 28, 2024
content-audit has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mia Li· Dec 28, 2024
Useful defaults in content-audit — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Soo Diallo· Dec 20, 2024
content-audit reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Evelyn Yang· Dec 8, 2024
We added content-audit from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Nikhil Bhatia· Dec 4, 2024
Solid pick for teams standardizing on skills: content-audit is focused, and the summary matches what you get after install.
- ★★★★★Nikhil Chawla· Nov 27, 2024
Registry listing for content-audit matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Evelyn Martin· Nov 27, 2024
Solid pick for teams standardizing on skills: content-audit is focused, and the summary matches what you get after install.
- ★★★★★Kofi Martin· Nov 23, 2024
We added content-audit from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ava Haddad· Nov 19, 2024
content-audit fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nia Bhatia· Nov 19, 2024
content-audit is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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