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smarttools/docs/EXAMPLES.md

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# Example Tools
This document contains all 28 pre-built SmartTools with their full configurations.
## Quick Install
```bash
# Install all example tools
curl -sSL https://raw.githubusercontent.com/yourusername/smarttools/main/examples/install.py | python3
smarttools refresh
```
## Text Processing Tools
### summarize
Condense long documents to key points.
```yaml
# ~/.smarttools/summarize/config.yaml
name: summarize
description: Condense long documents to key points
arguments:
- flag: --length
variable: length
default: "3-5 bullet points"
steps:
- type: prompt
prompt: |
Summarize the following text into {length}. Be concise and capture the key points:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat article.txt | summarize
cat book.txt | summarize --length "10 bullet points"
```
---
### translate
Translate text to any language.
```yaml
name: translate
description: Translate text to any language
arguments:
- flag: --lang
variable: lang
default: Spanish
steps:
- type: prompt
prompt: |
Translate the following text to {lang}. Only output the translation, nothing else:
{input}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
echo "Hello, world!" | translate --lang French
cat readme.md | translate --lang Japanese
```
---
### fix-grammar
Fix grammar and spelling errors.
```yaml
name: fix-grammar
description: Fix grammar and spelling errors
arguments: []
steps:
- type: prompt
prompt: |
Fix all grammar, spelling, and punctuation errors in the following text. Only output the corrected text, no explanations:
{input}
provider: opencode-deepseek
output_var: response
output: "{response}"
```
**Usage:**
```bash
echo "teh cat sat on teh mat" | fix-grammar
cat draft.txt | fix-grammar > fixed.txt
```
---
### simplify
Rewrite text for easier understanding.
```yaml
name: simplify
description: Rewrite text for easier understanding
arguments:
- flag: --level
variable: level
default: "5th grade reading level"
steps:
- type: prompt
prompt: |
Rewrite the following text for a {level}. Keep the meaning but use simpler words and shorter sentences:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat legal_document.txt | simplify
cat technical.md | simplify --level "non-technical reader"
```
---
### tone-shift
Change the tone of text.
```yaml
name: tone-shift
description: Change the tone of text
arguments:
- flag: --tone
variable: tone
default: professional
steps:
- type: prompt
prompt: |
Rewrite the following text in a {tone} tone. Keep the core message but adjust the style:
{input}
provider: opencode-deepseek
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat angry_email.txt | tone-shift --tone "calm and professional"
cat casual_note.txt | tone-shift --tone formal
```
---
### eli5
Explain like I'm 5.
```yaml
name: eli5
description: Explain like I'm 5
arguments: []
steps:
- type: prompt
prompt: |
Explain this like I'm 5 years old. Use simple words and fun analogies:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
echo "What is quantum computing?" | eli5
cat whitepaper.txt | eli5
```
---
### tldr
One-line summary.
```yaml
name: tldr
description: One-line summary
arguments: []
steps:
- type: prompt
prompt: |
Give a one-line TL;DR summary of this text:
{input}
provider: opencode-grok
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat long_article.txt | tldr
curl -s https://example.com | tldr
```
---
### expand
Expand bullet points to paragraphs.
```yaml
name: expand
description: Expand bullet points to paragraphs
arguments: []
steps:
- type: prompt
prompt: |
Expand these bullet points into well-written paragraphs:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat notes.txt | expand
echo "- Fast\n- Reliable\n- Easy to use" | expand
```
---
## Developer Tools
### explain-error
Explain error messages and stack traces.
```yaml
name: explain-error
description: Explain error messages and stack traces
arguments: []
steps:
- type: prompt
prompt: |
Explain this error/stack trace in plain English. What went wrong and how to fix it:
{input}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat error.log | explain-error
python script.py 2>&1 | explain-error
```
---
### explain-code
Explain what code does.
```yaml
name: explain-code
description: Explain what code does
arguments:
- flag: --detail
variable: detail
default: moderate
steps:
- type: prompt
prompt: |
Explain what this code does at a {detail} level of detail:
```
{input}
```
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat script.py | explain-code
cat complex.js | explain-code --detail "very detailed"
```
---
### review-code
Quick code review with suggestions.
```yaml
name: review-code
description: Quick code review with suggestions
arguments:
- flag: --focus
variable: focus
default: "bugs, security, and improvements"
steps:
- type: prompt
prompt: |
Review this code focusing on {focus}. Be concise and actionable:
```
{input}
```
provider: claude-sonnet
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat pull_request.diff | review-code
cat auth.py | review-code --focus "security vulnerabilities"
```
---
### gen-tests
Generate unit tests for code.
```yaml
name: gen-tests
description: Generate unit tests for code
arguments:
- flag: --framework
variable: framework
default: pytest
steps:
- type: prompt
prompt: |
Generate comprehensive unit tests for this code using {framework}. Include edge cases:
```
{input}
```
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat utils.py | gen-tests
cat api.js | gen-tests --framework jest
```
---
### docstring
Add docstrings to functions/classes.
```yaml
name: docstring
description: Add docstrings to functions/classes
arguments:
- flag: --style
variable: style
default: Google style
steps:
- type: prompt
prompt: |
Add {style} docstrings to all functions and classes in this code. Output the complete code with docstrings:
```
{input}
```
provider: opencode-deepseek
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat module.py | docstring
cat functions.py | docstring --style "NumPy style"
```
---
### commit-msg
Generate commit message from diff.
```yaml
name: commit-msg
description: Generate commit message from diff
arguments:
- flag: --style
variable: style
default: conventional commits
steps:
- type: prompt
prompt: |
Generate a concise {style} commit message for this diff. Just the message, no explanation:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
git diff --staged | commit-msg
git diff HEAD~1 | commit-msg --style "simple"
```
---
## Data Tools
### json-extract
Extract structured data as validated JSON.
```yaml
name: json-extract
description: Extract structured data as validated JSON
arguments:
- flag: --fields
variable: fields
default: any relevant fields
steps:
- type: prompt
prompt: |
Extract {fields} from this text as a JSON object. Output ONLY valid JSON, no markdown, no explanation:
{input}
provider: opencode-deepseek
output_var: raw_json
- type: code
code: |
import json
import re
text = raw_json.strip()
text = re.sub(r'^```json?\s*', '', text)
text = re.sub(r'\s*```$', '', text)
try:
parsed = json.loads(text)
validated = json.dumps(parsed, indent=2)
except json.JSONDecodeError as e:
validated = f"ERROR: Invalid JSON - {e}\nRaw output: {text[:500]}"
output_var: validated
output: "{validated}"
```
**Usage:**
```bash
echo "Price $49.99, SKU ABC-123" | json-extract --fields "price, sku"
cat invoice.txt | json-extract --fields "total, date, items"
```
---
### json2csv
Convert JSON to CSV format.
```yaml
name: json2csv
description: Convert JSON to CSV format
arguments: []
steps:
- type: prompt
prompt: |
Convert this JSON to CSV format. Output only the CSV, no explanation:
{input}
provider: opencode-deepseek
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat data.json | json2csv
echo '[{"name":"John","age":30}]' | json2csv
```
---
### extract-emails
Extract email addresses from text.
```yaml
name: extract-emails
description: Extract email addresses from text
arguments: []
steps:
- type: prompt
prompt: |
Extract all email addresses from this text. Output one email per line, nothing else:
{input}
provider: opencode-pickle
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat webpage.html | extract-emails
cat contacts.txt | extract-emails | sort -u
```
---
### extract-contacts
Extract contact info as structured CSV.
```yaml
name: extract-contacts
description: Extract contact info as structured CSV
arguments: []
steps:
- type: prompt
prompt: |
Extract all contact information (name, email, phone, company) from this text. Output as JSON array with objects having keys: name, email, phone, company. Use null for missing fields. Output ONLY the JSON array:
{input}
provider: opencode-pickle
output_var: contacts_json
- type: code
code: |
import json
import re
text = contacts_json.strip()
text = re.sub(r'^```json?\s*', '', text)
text = re.sub(r'\s*```$', '', text)
try:
contacts = json.loads(text)
lines = ['name,email,phone,company']
for c in contacts:
row = [
str(c.get('name') or ''),
str(c.get('email') or ''),
str(c.get('phone') or ''),
str(c.get('company') or '')
]
lines.append(','.join(f'"{f}"' for f in row))
csv_output = '\n'.join(lines)
except:
csv_output = f"Error parsing contacts: {text[:200]}"
output_var: csv_output
output: "{csv_output}"
```
**Usage:**
```bash
cat business_cards.txt | extract-contacts
cat meeting_notes.txt | extract-contacts > contacts.csv
```
---
### sql-from-text
Generate SQL from natural language.
```yaml
name: sql-from-text
description: Generate SQL from natural language
arguments:
- flag: --dialect
variable: dialect
default: PostgreSQL
steps:
- type: prompt
prompt: |
Generate a {dialect} SQL query for this request. Output only the SQL, no explanation:
{input}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
echo "get all users who signed up last month" | sql-from-text
echo "count orders by status" | sql-from-text --dialect MySQL
```
---
### safe-sql
Generate SQL with safety checks.
```yaml
name: safe-sql
description: Generate SQL with safety checks
arguments:
- flag: --dialect
variable: dialect
default: PostgreSQL
steps:
- type: prompt
prompt: |
Generate a {dialect} SELECT query for: {input}
Output ONLY the SQL query, no explanation.
provider: claude-haiku
output_var: raw_sql
- type: code
code: |
import re
sql = raw_sql.strip()
sql = re.sub(r'^```sql?\s*', '', sql)
sql = re.sub(r'\s*```$', '', sql)
dangerous = ['DROP', 'DELETE', 'TRUNCATE', 'UPDATE', 'INSERT', 'ALTER', 'CREATE', 'GRANT']
warnings = []
for keyword in dangerous:
if re.search(r'\b' + keyword + r'\b', sql, re.I):
warnings.append(f"WARNING: Contains {keyword}")
if warnings:
validated = '\n'.join(warnings) + '\n\n' + sql
else:
validated = sql
output_var: validated
output: "{validated}"
```
**Usage:**
```bash
echo "get active users" | safe-sql
echo "remove inactive accounts" | safe-sql # Will show WARNING
```
---
### parse-log
Summarize and analyze log files.
```yaml
name: parse-log
description: Summarize and analyze log files
arguments:
- flag: --focus
variable: focus
default: errors and warnings
steps:
- type: prompt
prompt: |
Analyze these logs focusing on {focus}. Summarize key issues and patterns:
{input}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat app.log | parse-log
tail -1000 /var/log/syslog | parse-log --focus "security events"
```
---
### csv-insights
Analyze CSV with sampled data for large files.
```yaml
name: csv-insights
description: Analyze CSV with sampled data for large files
arguments:
- flag: --question
variable: question
default: What patterns and insights can you find?
steps:
- type: code
code: |
import random
lines = input.strip().split('\n')
header = lines[0] if lines else ''
data_lines = lines[1:] if len(lines) > 1 else []
if len(data_lines) > 50:
sampled = random.sample(data_lines, 50)
sample_note = f"(Sampled 50 of {len(data_lines)} rows)"
else:
sampled = data_lines
sample_note = f"({len(data_lines)} rows)"
sampled_csv = header + '\n' + '\n'.join(sampled)
stats = f"Columns: {len(header.split(','))}, Rows: {len(data_lines)} {sample_note}"
output_var: sampled_csv,stats
- type: prompt
prompt: |
Analyze this CSV data. {stats}
Question: {question}
Data:
{sampled_csv}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat sales.csv | csv-insights
cat large_data.csv | csv-insights --question "What are the top trends?"
```
---
## Advanced Multi-Step Tools
### log-errors
Extract and explain errors from large log files.
```yaml
name: log-errors
description: Extract and explain errors from large log files
arguments: []
steps:
- type: code
code: |
import re
lines = input.split('\n')
errors = [l for l in lines if re.search(r'\b(ERROR|CRITICAL|FATAL|Exception|Traceback)\b', l, re.I)]
result = []
for i, line in enumerate(lines):
if re.search(r'\b(ERROR|CRITICAL|FATAL|Exception|Traceback)\b', line, re.I):
result.extend(lines[i:i+5])
extracted = '\n'.join(result[:200])
output_var: extracted
- type: prompt
prompt: |
Analyze these error log entries. Group by error type, explain likely causes, and suggest fixes:
{extracted}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
cat huge_app.log | log-errors
zcat archived.log.gz | log-errors
```
---
### diff-focus
Review only the added/changed code in a diff.
```yaml
name: diff-focus
description: Review only the added/changed code in a diff
arguments: []
steps:
- type: code
code: |
lines = input.split('\n')
result = []
for i, line in enumerate(lines):
if line.startswith('@@') or line.startswith('+++') or line.startswith('---'):
result.append(line)
elif line.startswith('+') and not line.startswith('+++'):
result.append(line)
extracted = '\n'.join(result)
output_var: extracted
- type: prompt
prompt: |
Review these added lines of code. Focus on bugs, security issues, and improvements:
{extracted}
provider: claude-haiku
output_var: response
output: "{response}"
```
**Usage:**
```bash
git diff | diff-focus
git diff HEAD~5 | diff-focus
```
---
### changelog
Generate changelog from git commits.
```yaml
name: changelog
description: Generate changelog from git commits
arguments:
- flag: --since
variable: since
default: last week
steps:
- type: code
code: |
lines = input.strip().split('\n')
commits = []
for line in lines:
if line.strip() and not line.startswith('commit '):
commits.append(line.strip())
git_log = '\n'.join(commits[:100])
output_var: git_log
- type: prompt
prompt: |
Generate a user-friendly changelog from these git commits. Group by category (Features, Fixes, Improvements, etc). Use markdown with bullet points:
{git_log}
provider: opencode-pickle
output_var: changelog_raw
- type: code
code: |
from datetime import datetime
header = f"""# Changelog
Generated: {datetime.now().strftime('%Y-%m-%d')}
"""
formatted = header + changelog_raw
output_var: formatted
output: "{formatted}"
```
**Usage:**
```bash
git log --oneline -50 | changelog
git log --since="2024-01-01" --oneline | changelog
```
---
### code-validate
Generate and validate Python code.
```yaml
name: code-validate
description: Generate and validate Python code
arguments:
- flag: --task
variable: task
default: ""
steps:
- type: prompt
prompt: |
Write Python code to: {task}
Context/input data:
{input}
Output ONLY the Python code, no markdown, no explanation.
provider: claude-haiku
output_var: raw_code
- type: code
code: |
import ast
import re
code = raw_code.strip()
code = re.sub(r'^```python?\s*', '', code)
code = re.sub(r'\s*```$', '', code)
try:
ast.parse(code)
validated = code
except SyntaxError as e:
validated = f"# SYNTAX ERROR at line {e.lineno}: {e.msg}\n# Fix needed:\n\n{code}"
output_var: validated
output: "{validated}"
```
**Usage:**
```bash
echo "list of numbers: 1,2,3,4,5" | code-validate --task "calculate the sum"
cat data.json | code-validate --task "parse and find the maximum value"
```
---
## Writing Your Own Tools
### Basic Structure
```yaml
name: my-tool
description: What this tool does
arguments:
- flag: --option
variable: option_name
default: "default value"
steps:
- type: prompt
prompt: |
Your prompt here with {input} and {option_name}
provider: opencode-pickle
output_var: response
output: "{response}"
```
### Multi-Step Structure
```yaml
name: my-pipeline
description: Multi-step tool
steps:
# Step 1: Preprocess with code
- type: code
code: |
# Python code here
processed = input.upper()
output_var: processed
# Step 2: AI processing
- type: prompt
prompt: "Analyze: {processed}"
provider: claude-haiku
output_var: analysis
# Step 3: Post-process with code
- type: code
code: |
result = f"RESULT:\n{analysis}"
output_var: result
output: "{result}"
```
### Tips
1. **Use cheap providers** for simple tasks (`opencode-pickle`)
2. **Use code steps** to validate AI output
3. **Preprocess large inputs** to reduce tokens
4. **Test with mock** before using real AI: `--provider mock`
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