agentsclimarketplace

Content audit

Skill kjuhwa/skills-hub/skills/qa/content-audit

Audit GDD-specified content counts against implemented content. Identifies what's planned vs built.From its SKILL.md

Install
npx -y skills add kjuhwa/skills-hub --skill content-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

7.3 KB, ~1.8k tokens by cl100k_base, as published. Nobody here has run it

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.

  2. L0 pre-scan: Before full-reading any GDDs, Grep all GDD files for ## Summary sections 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.

  3. Full-read in-scope GDD files (or the single system GDD if a system name was given).

  4. 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)
  5. Build a content inventory table from the extracted data:

    SystemContent TypeSpecified Count/ListSource 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, .yaml data 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, .asset data files

Abilities / Skills / Spells:

  • Glob assets/data/**/abilities/**, assets/data/**/skills/**, assets/data/**/spells/**
  • Look for .json, .tres, .asset data 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, .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 /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 STARTED and MVP-tagged → "Run /design-system [name] to add missing content counts to the GDD before implementation begins."
  • If total gap is >50% → "Run /sprint-plan to allocate content work across upcoming sprints."
  • If backlog stories are needed → "Run /create-stories [epic-slug] for each HIGH PRIORITY gap."
  • If --summary was used → "Run /content-audit (no flag) to write the full report to docs/."

Verdict: COMPLETE — content audit finished.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most audit compliance skills give in ~1.8k tokens

Counted across 937 of the 1,487 authors here whose files we hold, read 2026-08-07

  • Fetch latest guidelines before each reviewin 43 of 937, across 3 files
  • Group findings by severityin 43 of 937
  • Check files against all fetched rulesin 42 of 937, across 2 files
  • Output findings in terse file:line formatin 41 of 937, across 3 files
  • Ask user which files to review if none specifiedin 41 of 937, across 3 files
  • Read specified files or prompt user for filesin 39 of 937, across 1 file
  • Generate the audit reportin 33 of 937, across 30 files
  • Assign a severity to every findingin 25 of 937
  • Run automated accessibility scansin 23 of 937, across 13 files
  • Output a markdown audit reportin 22 of 937
  • Map findings to WCAG criteriain 20 of 937, across 10 files
  • Confirm audit scopein 19 of 937, across 9 files

Said here and by no other author read

  • parse the invocation argument
  • read the systems index
  • grep design documents for summary sections
  • extract explicit content counts or lists
  • scan directories for implemented content files
  • calculate the content gap

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 326,790. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.