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Skill Gap Analyzer

ASecurity

Analyzes project requirements to identify missing skills and automatically creates them. Enforces MCP Code Execution pattern for skills that use external tools. This skill should be used when starting a new project to ensure all required skills exist.

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  • Added February 7, 2026
developmenttypescriptpythongobashsqlreactnextjsnodenodejsexpress

Works with

  • claude code
  • cli
  • api
  • mcp

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Scanned February 12, 2026

npx -y skills add Wania-Kazmi/claude-code-autonomous-agent-workflow --skill skill-gap-analyzer --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: skill-gap-analyzer
description: |
  Analyzes project requirements to identify missing skills and automatically creates them.
  Enforces MCP Code Execution pattern for skills that use external tools.
  This skill should be used when starting a new project to ensure all required skills exist.
author: Claude Code
version: 2.1.0
mcp-pattern: enforced
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Bash
---

# Skill Gap Analyzer

Automatically identifies and creates missing skills based on project requirements.
**Enforces MCP Code Execution pattern** for token efficiency when skills use external tools.

---

## MANDATORY EXECUTION STEPS

When this skill is invoked, you MUST execute these steps IN ORDER:

### Step A: Read Requirements File
```
Read the requirements file passed as argument
```

### Step B: Detect Technologies
Scan for these keywords and mark detected:

| Technology | Keywords to Search |
|------------|-------------------|
| React | "react", "jsx", "component" |
| Next.js | "next.js", "nextjs", "next" |
| Express | "express", "node api", "nodejs backend" |
| FastAPI | "fastapi", "python api", "uvicorn" |
| PostgreSQL | "postgresql", "postgres", "pg" |
| MongoDB | "mongodb", "mongo", "mongoose" |
| Prisma | "prisma", "orm" |
| Docker | "docker", "container", "dockerfile" |
| TypeScript | "typescript", "ts", ".tsx" |
| Jest | "jest", "test", "testing" |
| Playwright | "playwright", "e2e", "end-to-end" |

### Step C: List Existing Skills
```bash
ls -la .claude/skills/
```

### Step D: Create Missing Skills (WITH GUARDRAILS)

**⚠️ CRITICAL RULES:**
```
╔═══════════════════════════════════════════════════════════════════════════╗
║  SKILL CREATION RULES - NEVER VIOLATE                                      ║
╠═══════════════════════════════════════════════════════════════════════════╣
║  ✓ ONLY create skills in: .claude/skills/{name}/SKILL.md                  ║
║  ✗ NEVER create: skill-lab/, workspace/, temp/, output/                   ║
║  ✗ NEVER create: .claude/ inside another directory                        ║
║  ✗ NEVER create: nested directories like .claude/.claude/                 ║
║  ✗ NEVER overwrite existing skills - SKIP if exists                       ║
╚═══════════════════════════════════════════════════════════════════════════╝
```

For EACH detected technology that doesn't have a skill:

1. **CHECK if skill exists first:**
   ```bash
   if [ -f ".claude/skills/{tech}-patterns/SKILL.md" ]; then
       echo "SKIP: {tech}-patterns already exists"
       continue
   fi
   ```

2. Create directory: `mkdir -p .claude/skills/{tech}-patterns`
   - ONLY in `.claude/skills/` - NOWHERE else

3. Create SKILL.md with the template below

4. Add technology-specific content

### Step E: Generate Report
Create `.specify/skill-gap-report.json` with results

---

## Core Workflow

### 1. Analyze Requirements

Extract technology requirements from the project:

```python
def analyze_requirements(requirements_text: str) -> dict:
    """Extract technologies and patterns from requirements."""

    patterns = {
        "fastapi": ["fastapi", "python api", "rest api python"],
        "nextjs": ["next.js", "nextjs", "react frontend", "frontend"],
        "express": ["express", "node.js api", "nodejs"],
        "postgresql": ["postgresql", "postgres", "sql database"],
        "mongodb": ["mongodb", "mongo", "nosql", "document database"],
        "kafka": ["kafka", "event streaming", "message queue"],
        "graphql": ["graphql", "graph api"],
        "docker": ["docker", "container", "dockerfile"],
        "kubernetes": ["kubernetes", "k8s", "kubectl"],
        "github-actions": ["github actions", "ci/cd", "pipeline"],
    }

    # MCP-related patterns (require code execution)
    mcp_patterns = {
        "google-drive": ["google drive", "gdrive", "docs api"],
        "salesforce": ["salesforce", "crm", "sfdc"],
        "slack": ["slack", "slack api", "messaging"],
        "github-api": ["github api", "repository api", "issues api"],
        "database-query": ["query database", "sql queries", "data extraction"],
        "spreadsheet": ["spreadsheet", "excel", "csv processing", "sheets"],
        "email": ["email", "smtp", "mail api"],
        "storage": ["s3", "cloud storage", "blob storage"],
    }

    detected = []
    mcp_required = []
    text_lower = requirements_text.lower()

    for tech, keywords in patterns.items():
        if any(kw in text_lower for kw in keywords):
            detected.append(tech)

    for mcp, keywords in mcp_patterns.items():
        if any(kw in text_lower for kw in keywords):
            mcp_required.append(mcp)

    return {
        "technologies": detected,
        "mcp_integrations": mcp_required,
        "requires_code_execution": len(mcp_required) > 0
    }
```

### 2. Map Technologies to Skills

| Technology | Required Skill | MCP Pattern |
|------------|---------------|-------------|
| fastapi | `fastapi-generator` | No |
| nextjs | `nextjs-generator` | No |
| express | `express-generator` | No |
| postgresql | `postgres-setup` | No |
| mongodb | `mongodb-setup` | No |
| kafka | `kafka-setup` | No |
| graphql | `graphql-generator` | No |
| docker | `docker-generator` | No |
| kubernetes | `k8s-generator` | No |
| github-actions | `ci-cd-generator` | No |
| google-drive | `gdrive-integration` | **YES** |
| salesforce | `salesforce-integration` | **YES** |
| slack | `slack-integration` | **YES** |
| spreadsheet | `spreadsheet-processor` | **YES** |
| database-query | `data-extractor` | **YES** |

### 3. Check Existing Skills

```python
def check_existing_skills(required_skills: list) -> dict:
    """Check which skills exist and which are missing."""

    existing = []
    missing = []

    for skill in required_skills:
        skill_path = f".claude/skills/{skill}/SKILL.md"
        if Path(skill_path).exists():
            existing.append(skill)
        else:
            missing.append(skill)

    return {"existing": existing, "missing": missing}
```

### 4. Detect MCP Pattern Requirements

```python
def requires_mcp_pattern(skill_name: str, requirements: dict) -> bool:
    """Determine if a skill needs MCP Code Execution pattern."""

    mcp_skill_patterns = [
        "integration", "connector", "api-client",
        "extractor", "processor", "sync"
    ]

    # Check if skill name suggests MCP usage
    if any(p in skill_name for p in mcp_skill_patterns):
        return True

    # Check if requirements mention external APIs
    mcp_keywords = [
        "external api", "third-party", "integration",
        "fetch data", "sync data", "import from",
        "export to", "connect to"
    ]

    req_text = str(requirements).lower()
    return any(kw in req_text for kw in mcp_keywords)
```

### 5. Auto-Create Missing Skills

For each missing skill, generate using appropriate template:

**Standard Skill Template:**
```markdown
---
name: {skill-name}
description: |
  {Description}. Triggers: {keywords}
version: 1.0.0
---

# {Skill Title}

## Workflow
1. {Step 1}
2. {Step 2}

## Code Templates
...
```

**MCP Code Execution Skill Template:**
```markdown
---
name: {skill-name}
description: |
  {Description}. Uses MCP Code Execution for 98% token efficiency.
  Triggers: {keywords}
version: 1.0.0
mcp-pattern: code-execution
---

# {Skill Title}

## MCP Servers Used
- `{server}`: {tools}

## Execution Pattern

This skill uses **MCP Code Execution**:
1. Agent writes code to `./workspace/task.ts`
2. Code calls MCP tools in execution environment
3. Only final summary returns to model

## Directory Structure
\`\`\`
{skill-name}/
├── SKILL.md
├── servers/
│   └── {server-name}/
│       ├── index.ts
│       └── {tool}.ts
├── scripts/
│   └── execute.py
└── workspace/
\`\`\`

## Progressive Disclosure
\`\`\`bash
ls ./servers/                    # List MCP servers
ls ./servers/{server}/           # List tools
cat ./servers/{server}/{tool}.ts # Read definition
\`\`\`

## Code Template
\`\`\`typescript
import * as server from './servers/{server}';

async function main() {
  const data = await server.{tool}({ ... });
  const filtered = data.filter(item => item.relevant);
  console.log(\`Processed \${filtered.length} items\`);
}
main();
\`\`\`

## Validation
- [ ] Code executes outside model context
- [ ] Only summary returned (~100 tokens)
- [ ] Large data processed in execution env
```

### 6. Output

Generate report:

```json
{
  "analyzed_requirements": "path/to/requirements.md",
  "technologies_detected": ["fastapi", "postgresql", "kafka"],
  "mcp_integrations_detected": ["google-drive", "salesforce"],
  "skills_required": [
    {"name": "fastapi-generator", "mcp_pattern": false},
    {"name": "gdrive-integration", "mcp_pattern": true}
  ],
  "skills_existing": ["fastapi-generator"],
  "skills_created": [
    {"name": "postgres-setup", "mcp_pattern": false},
    {"name": "gdrive-integration", "mcp_pattern": true}
  ],
  "mcp_pattern_enforced": true,
  "ready_to_build": true
}
```

## MCP Pattern Enforcement Rules

When generating skills that use external tools/APIs:

1. **MUST use Code Execution pattern** if:
   - Skill fetches large documents/datasets
   - Skill chains multiple API calls
   - Skill processes external data

2. **Skill structure MUST include**:
   - `servers/` directory with tool wrappers
   - `workspace/` for intermediate files
   - Progressive disclosure (load tools on-demand)

3. **Generated code MUST**:
   - Run outside model context
   - Filter/aggregate before returning
   - Return only summaries (~100 tokens)

4. **SKILL.md MUST include**:
   - `mcp-pattern: code-execution` in frontmatter
   - Tool discovery commands
   - Code template with console.log for results

## Token Efficiency Targets

| Skill Type | Max Tokens |
|------------|------------|
| Standard skill | 500 |
| MCP skill (code execution) | 200 |
| Tool discovery | 100 |
| Result summary | 100 |

Files in this skill

  • SKILL.md10.2 KB
  • scripts/analyzer.py9.8 KB

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