content-audit
Skill1 starsChanged 3 months agoMITView on GitHub
Audit GDD-specified content counts against implemented content. Identifies what's planned vs built.
25 other projects use a version of this, 6 of them edited.
Adopted by
Most recently taken up by
- risukisu/marketing-skillstheir own version, first seen Nov 8, 2026
- striderZA/OpenCodeGameStudiosword for word, first seen Nov 4, 2026
- robritacca-dotcom/rift-dstheir own version, first seen Nov 1, 2026
- brainbytes-dev/everything-claude-marketingtheir own version, first seen Nov 1, 2026
- robritacca-dotcom/design-systemtheir own version, first seen Oct 28, 2026
- microsoft/frontier-ghcp-rvastheir own version, first seen Oct 25, 2026
Other versions25 projects use a version of this.
Word for word · 2
- striderZA/OpenCodeGameStudios★ 118100% same
- lilangMax/ClaudeCodeGameStudios★ 8100% same
Edited · 6
- Donchitos/Claude-Code-Game-Studios★ 27k39% same
- dawn840705/codex-code-studios★ 17100% same
- hongyuanc/codex-game-studios★ 584% same
- HunLuanZhiZhu/Game-Studios-Plugin★ 199% same
- venus2099/codex-game-studios★ 140% same
- ShiningPlague/shiningplague-studio★ 042% same
Wrote their own version · 17
- Ootto-AI/claude-content-skills★ 417same name
- OffchainLabs/arbitrum-docs★ 252same name
- cenconq25/claude-code-app-studio★ 40same name
- huifer/AdSense-Readiness-Benchmark★ 14same name
- brainbytes-dev/everything-claude-marketing★ 9same name
- robritacca-dotcom/rift-ds★ 9same name
- greglas75/zuvo★ 7same name
- Muvon/octomind-tap★ 6same name
- risukisu/marketing-skills★ 6same name
- microsoft/frontier-ghcp-rvas★ 5same name
7 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository90 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- adoptSkill
- api-cost-gateSkill
- architecture-decisionSkill
- architecture-reviewSkill
- art-bibleSkill
- asset-auditSkill
- asset-specSkill
- balance-checkSkill
- brainstormSkill
- bug-reportSkill
- bug-triageSkill
- changelogSkill
- code-reviewSkill
- consistency-checkSkill
- create-architectureSkill
- create-control-manifestSkill
- create-epicsSkill
- create-prdSkill
- create-storiesSkill
- day-one-patchSkill
- design-reviewSkill
- design-systemSkill
- dev-storySkill
- doc-relinkSkill
- estimateSkill
- gate-checkSkill
- governance-bible-initSkill
- helpSkill
- hotfixSkill
- humanize-koreanSkill
- humanize-redoSkill
- humanizeSkill
- launch-checklistSkill
- legacy-purgeSkill
- lesson-logSkill
- lesson-reviewSkill
- localizeSkill
- map-systemsSkill
- milestone-reviewSkill
- onboardSkill
- patch-notesSkill
- perf-profileSkill
- playtest-reportSkill
- product-conceptSkill
- project-stage-detectSkill
- propagate-design-changeSkill
- prototypeSkill
- qa-planSkill
- quick-designSkill
- regression-suiteSkill
- release-checklistSkill
- remove-bgSkill
- retrospectiveSkill
- reverse-documentSkill
- review-all-gddsSkill
- scope-checkSkill
- security-auditSkill
- self-loopSkill
- setup-engineSkill
- The first 60 shown.
The file
Show its rules and text
We split this skill into the rules it gives an agent
17 rules. 0 are common, 7 are distinctive, and 10 are very specific to this project.
0
Common
Most of the 22 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 10
When this skill is invoked:
- Distinctive: line 13
No argument → full audit across all systems
- Very specific: line 24
L0 pre-scan: Before full-reading any GDDs, Grep all GDD files for ## Summary sections plus common content-count keywords:
- Distinctive: line 37
For each GDD, extract explicit content counts or lists: Look for patterns like:
- Very specific: line 65
Look for scene files in subdirectories named levels/, areas/, maps/, worlds/, stages/
- Very specific: line 72
Look for .json, .tres, .asset, .yaml data files defining entity stats
- Distinctive: line 73
Look for scene/prefab files in character subdirectories
- Very specific: line 78
Look for .json, .tres, .asset data files
- Very specific: line 91
Look for .json, .yaml definition files
- Distinctive: line 135
If yes, write the file:
- Distinctive: line 180
After writing the report, ask:
- Very specific: line 184
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 …
- Distinctive: line 196
After the audit, recommend the highest-value follow-up actions:
- Very specific: line 198
If any system is NOT STARTED and MVP-tagged → "Run /design-system [name] to add missing content counts to the GDD before implementation …
- Very specific: line 200
If total gap is >50% → "Run /sprint-plan to allocate content work across upcoming sprints."
- Very specific: line 201
If backlog stories are needed → "Run /create-stories [epic-slug] for each HIGH PRIORITY gap."
- Very specific: line 202
If --summary was used → "Run /content-audit (no flag) to write the full report to docs/."
“Common” is measured: kept by at least 6 in 10 of the 22 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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:
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.Grep pattern="(## Summary|N enemies|N levels|N items|N abilities|enemy types|item types)" glob="design/gdd/*.md" output_mode="files_with_matches" - 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.
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