suggesting-tooling

Analyzes a codebase and suggests custom Claude Code skills and subagents to improve development workflow. Use when user wants tooling suggestions, automation ideas, or asks "what skills would help this project".

242 stars

Best use case

suggesting-tooling is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Analyzes a codebase and suggests custom Claude Code skills and subagents to improve development workflow. Use when user wants tooling suggestions, automation ideas, or asks "what skills would help this project".

Analyzes a codebase and suggests custom Claude Code skills and subagents to improve development workflow. Use when user wants tooling suggestions, automation ideas, or asks "what skills would help this project".

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "suggesting-tooling" skill to help with this workflow task. Context: Analyzes a codebase and suggests custom Claude Code skills and subagents to improve
development workflow. Use when user wants tooling suggestions, automation ideas, or
asks "what skills would help this project".

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/suggesting-tooling/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/brendanshields/suggesting-tooling/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/suggesting-tooling/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How suggesting-tooling Compares

Feature / Agentsuggesting-toolingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Analyzes a codebase and suggests custom Claude Code skills and subagents to improve development workflow. Use when user wants tooling suggestions, automation ideas, or asks "what skills would help this project".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Suggesting Tooling

Analyzes codebases to suggest custom skills and agents for workflow automation.

## Quick Start

1. Scan codebase for patterns (languages, frameworks, workflows)
2. Match patterns to skill/agent templates
3. Present suggestions with rationale
4. Generate approved tooling using creating-skills/creating-agents

## Workflow

```
Progress:
- [ ] Analyze codebase patterns
- [ ] Match to tooling templates
- [ ] Present suggestions
- [ ] Generate approved items
```

### Step 1: Analyze Codebase

Run lightweight analysis:

```bash
# Language detection
find . -type f -name "*.ts" -o -name "*.js" -o -name "*.py" | head -100

# Framework detection
ls package.json pyproject.toml Cargo.toml go.mod 2>/dev/null

# Workflow detection
ls .github/workflows/ .gitlab-ci.yml Dockerfile 2>/dev/null

# Existing tooling
ls .claude/skills/ .claude/agents/ 2>/dev/null
```

Collect:
- Primary language(s)
- Framework(s) in use
- Build/test tooling
- CI/CD setup
- Existing .claude/ configuration

### Step 2: Pattern Matching

Match detected patterns to suggestions:

| Signal | Skill Suggestion | Agent Suggestion |
|--------|------------------|------------------|
| Jest/Pytest/Mocha | testing-code | - |
| REST routes | - | api-testing |
| Prisma/migrations | db-migrations | - |
| Dockerfile | deploying-code | - |
| ESLint/Prettier | linting-code | - |
| Auth patterns | - | security-review |
| Many .md files | documenting-code | - |
| PR workflow | - | code-reviewer |

See [patterns/skills.md](patterns/skills.md) and [patterns/agents.md](patterns/agents.md) for complete mappings.

### Step 3: Present Suggestions

Format suggestions for user review:

```markdown
## Tooling Suggestions for {project}

Based on analysis of your codebase:
- Language: {detected}
- Framework: {detected}
- Existing tooling: {count} skills, {count} agents

### Recommended Skills

| # | Skill | Why | Priority |
|---|-------|-----|----------|
| 1 | {name} | {rationale} | P1 |
| 2 | {name} | {rationale} | P2 |

### Recommended Agents

| # | Agent | Why | Priority |
|---|-------|-----|----------|
| 1 | {name} | {rationale} | P1 |
```

Then ask user which to generate.

### Step 4: Generate Tooling

For each approved item:

**Skills** - Invoke creating-skills:
```
Use the creating-skills skill to create a {name} skill.

Purpose: {rationale}
Detected context:
- Framework: {framework}
- Test runner: {runner}
- Patterns: {patterns}

Generate a focused skill for this project.
```

**Agents** - Invoke creating-agents:
```
Use the creating-agents skill to create a {name} agent.

Purpose: {rationale}
Suggested tools: {tools}
Detected context:
- Project type: {type}
- Workflows: {workflows}

Generate a focused agent for this project.
```

## Pattern Categories

### Testing
- **Signals**: jest.config, pytest.ini, mocha, test/ directory
- **Suggest**: testing-code skill
- **Priority**: P1 if tests exist but no skill

### API Development
- **Signals**: Express routes, FastAPI, REST patterns
- **Suggest**: api-testing agent
- **Priority**: P1 if API-heavy project

### Database
- **Signals**: Prisma, TypeORM, migrations/
- **Suggest**: db-migrations skill
- **Priority**: P2

### DevOps
- **Signals**: Dockerfile, docker-compose, CI configs
- **Suggest**: deploying-code skill
- **Priority**: P2 if no deployment automation

### Code Quality
- **Signals**: ESLint, Prettier, pre-commit
- **Suggest**: linting-code skill
- **Priority**: P3

### Security
- **Signals**: Auth middleware, JWT, OAuth
- **Suggest**: security-review agent
- **Priority**: P1 for auth-heavy projects

See [reference.md](reference.md) for detailed pattern definitions.

## Gap Analysis

Compare detected needs against existing .claude/ configuration:

```
Detected workflows:     Existing tooling:
- Testing (Jest)        - (none)
- API (Express)         - (none)
- CI (GitHub Actions)   - (none)

Gaps: testing, api-testing, deployment
```

Only suggest tooling that fills gaps.

## Output Format

After generation, report:

```markdown
## Tooling Created

| Type | Name | Location |
|------|------|----------|
| Skill | testing-code | .claude/skills/testing-code/ |
| Agent | code-reviewer | .claude/agents/code-reviewer.md |

### Restart Required

New skills and agents require a Claude restart to be available.

To continue where you left off:
\`\`\`bash
claude --continue
\`\`\`

### Next Steps

1. Restart Claude to load new tooling
2. Run `claude --continue` to resume
3. Review generated tooling in .claude/
4. Test skills with sample workflows
```

## Limits

- Maximum 5 suggestions per category
- Require explicit approval before generating
- Skip suggestions for existing tooling
- Prioritize by impact (P1 first)

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