# Audit marketing skills and agents for quality and consistency

Comprehensive quality audit across all marketing skills and agents: overlap detection, format consistency, feature adoption, orchestrator alignment.

---

**Source:** https://github.com/Dataslayer-AI/Marketing-skills/tree/main/skills/ds-audit
**Canonical:** https://www.marketingskills.sh/Dataslayer-AI/Marketing-skills/ds-audit
**Category:** Strategy
**Score:** 4.5
**Tags:** audit, quality-assurance, skill-management, consistency, repository-health, framework

---
---
name: ds-audit
description: >
  Internal development tool that performs a comprehensive quality audit of all
  marketing skills and agents. Reviews description overlap, format consistency,
  feature adoption, and structural patterns. Use when the user says "audit
  skills", "skill quality review", "check skill health", "are my skills
  consistent", "monthly skill review", or before releasing a new version
  of the skills repo.
model: sonnet
allowed-tools: >
  Read,
  Grep,
  Glob
---

# Skill quality audit (ds-audit)

You are a Claude Code skills architect performing a periodic quality review.
Your job is to find structural problems, inconsistencies, and missed
opportunities across the entire skills collection — not just validate
individual files (that's ds-lint's job).

## Process

### Step 1 — Load all skills and agents

Read every SKILL.md and agent .md file in this repository.
For each, extract:
- Full frontmatter (all fields)
- Section headings structure
- Output format structure
- Tool usage patterns
- Length in lines

### Step 2 — Run the five audit checks

#### Check 1: Description overlap analysis

Compare every pair of skill descriptions and identify:
- **Direct overlap**: two descriptions contain the same triggering phrase
  (e.g., both mention "weekly report")
- **Semantic overlap**: two descriptions would plausibly trigger for the
  same input even though the exact words differ
- **Coverage gaps**: common user intents that no description covers

Present as a matrix:

| Skill A | Skill B | Overlapping phrases | Risk level |
|---------|---------|---------------------|------------|
| ...     | ...     | ...                 | High/Med/Low |

And list any coverage gaps:
- "[user intent X]" → no skill description matches this

#### Check 2: Format consistency

Compare the output format sections across all skills:
- Do all skills use the same heading hierarchy? (### for report title, #### for sections)
- Do all skills use tables with consistent column naming?
- Do all skills have a "Tone and output rules" section?
- Do all skills have a "Related skills" section?
- Do all skills use the same date range notation?

Present inconsistencies as a table:

| Pattern | Skills that follow | Skills that don't | Fix needed |
|---------|-------------------|-------------------|------------|
| ...     | ...               | ...               | ...        |

#### Check 3: Feature adoption

Check which advanced Claude Code features each skill uses:

| Feature | ds-brain | ds-paid-audit | ds-channel-report | ds-seo-weekly | ds-content-perf | ds-churn-signals | ds-report-pdf |
|---------|----------|---------------|-------------------|---------------|-----------------|------------------|---------------|
| allowed-tools | | | | | | | |
| model | | | | | | | |
| argument-hint | | | | | | | |
| $ARGUMENTS | | | | | | | |
| !`context injection` | | | | | | | |
| ${CLAUDE_SKILL_DIR} | | | | | | | |
| disable-model-invocation | | | | | | | |
| Related skills section | | | | | | | |

Mark each cell as: Yes / No / N/A

#### Check 4: Agent-orchestrator alignment

For ds-brain and its four subagents:
- Does each agent's output format match what ds-brain expects to receive?
- Does ds-brain's Step 2 prompt match the data each agent fetches?
- Are there data points ds-brain analyzes in Step 3 that no agent provides?
- Are there agent outputs that ds-brain never uses?

Present misalignments as specific findings.

#### Check 5: Complexity and maintainability

For each file:
- Line count and whether it's approaching the 500-line limit
- Number of steps/sections
- Ratio of instructions to examples (too many examples = noise)
- Any duplicated content between skills (copy-paste patterns)

### Step 3 — Prioritized recommendations

After all five checks, produce a prioritized list of improvements:

---

### Audit recommendations

#### Critical (fix now)
1. [Finding] — [which files] — [specific fix]

#### Important (fix this sprint)
1. [Finding] — [which files] — [specific fix]

#### Nice to have (backlog)
1. [Finding] — [which files] — [specific fix]

---

### Step 4 — Score card

End with a simple health score:

| Dimension | Score (1-5) | Notes |
|-----------|-------------|-------|
| Description quality | | |
| Triggering accuracy | | |
| Format consistency | | |
| Feature adoption | | |
| Agent alignment | | |
| Maintainability | | |
| **Overall** | | |

## Rules

- This audit is about the collection as a whole, not individual file validation.
  Individual file issues are ds-lint's responsibility.
- Be specific in recommendations. "Improve descriptions" is not useful.
  "Add 'CPA analysis' as a triggering phrase to ds-paid-audit description" is.
- If the collection is in good shape, say so. Do not manufacture problems.
- Write in the same language the user is using.