Standardise

Documentation and examples standardisation (FDEP) CLI commands

Overview

The standardise command provides tools for managing documentation and examples consistency across the PraisonAI project. It implements the Feature Docs/Examples Protocol (FDEP) to ensure all features have proper documentation and examples.

Commands

Check

Check for standardisation issues without making changes.

praisonai standardise check [OPTIONS]

Options:

Option	Type	Default	Description
--path, -p	string	.	Project root path
--feature	string	-	Specific feature slug to check
--scope	choice	all	Scope: all, docs, examples, sdk, cli
--ci	flag	false	CI mode with exit codes

Example:

# Check all features
praisonai standardise check

# Check specific feature
praisonai standardise check --feature guardrails

# CI mode (returns exit code 1 if issues found)
praisonai standardise check --ci

Report

Generate a detailed standardisation report.

praisonai standardise report [OPTIONS]

Options:

Option	Type	Default	Description
--path, -p	string	.	Project root path
--format, -f	choice	text	Format: text, json, markdown
--output, -o	string	-	Output file path

Example:

# Text report to stdout
praisonai standardise report

# Markdown report to file
praisonai standardise report --format markdown --output report.md

# JSON report for automation
praisonai standardise report --format json

Fix

Fix standardisation issues by creating missing artifacts.

praisonai standardise fix [OPTIONS]

Options:

Option	Type	Default	Description
--path, -p	string	.	Project root path
--feature	string	-	Specific feature slug to fix
--apply	flag	false	Actually apply changes (default: dry-run)
--no-backup	flag	false	Don’t create backups

Example:

# Preview what would be fixed (dry-run)
praisonai standardise fix --feature guardrails

# Actually apply fixes
praisonai standardise fix --feature guardrails --apply

Init

Initialise a new feature with all required artifacts.

praisonai standardise init FEATURE [OPTIONS]

Arguments:

Argument	Description
FEATURE	Feature slug to initialise

Options:

Option	Type	Default	Description
--path, -p	string	.	Project root path
--apply	flag	false	Actually create files

Example:

# Preview what would be created
praisonai standardise init my-feature

# Create the files
praisonai standardise init my-feature --apply

AI

AI-powered generation of documentation and examples using LLM.

Real, Runnable Examples: The AI generator creates actual working code, not templates. Examples are verified by execution before being written - if the code doesn’t run, it won’t be saved.

praisonai standardise ai FEATURE [OPTIONS]

Arguments:

Argument	Description
FEATURE	Feature slug to generate content for

Options:

Option	Type	Default	Description
--type, -t	choice	all	Type: docs, examples, all
--apply	flag	false	Actually create files
--verify	flag	false	Additional AI content review
--model	string	gpt-4o-mini	LLM model to use
--path, -p	string	.	Project root path

Features:

• Real Examples: Generates working code with mock data, not placeholder templates
• Execution Verification: Examples are run before writing to ensure they work
• Auto-Retry: If code fails, the AI attempts to fix it (up to 2 retries)
• External Library Handling: Examples requiring external libraries are marked but still saved

Example:

# Preview AI-generated docs
praisonai standardise ai guardrails --type docs

# Generate and apply examples with verification
praisonai standardise ai guardrails --type examples --apply --verify

# Use a different model
praisonai standardise ai guardrails --model gpt-4o --apply

Verification Output:

📝 Generating example_basic...
  ✅ Code verified: runs successfully
  ✓ Created: examples/guardrails/guardrails-basic.py

📝 Generating example_advanced...
  ✅ Code verified: runs successfully
  ✓ Created: examples/guardrails/guardrails-advanced.py

Checkpoint

Create an undo checkpoint before making changes.

praisonai standardise checkpoint [OPTIONS]

Options:

Option	Type	Default	Description
--message, -m	string	-	Checkpoint message
--path, -p	string	.	Repository path

Example:

# Create checkpoint with message
praisonai standardise checkpoint -m "Before AI generation"

Undo

Undo to a previous checkpoint.

praisonai standardise undo [OPTIONS]

Options:

Option	Type	Default	Description
--checkpoint	string	-	Specific checkpoint ID
--list	flag	false	List available checkpoints
--path, -p	string	.	Repository path

Example:

# List available checkpoints
praisonai standardise undo --list

# Undo to specific checkpoint
praisonai standardise undo --checkpoint standardise-checkpoint-20240101-120000

# Undo to previous checkpoint
praisonai standardise undo

Redo

Redo after an undo operation.

praisonai standardise redo [OPTIONS]

Options:

Option	Type	Default	Description
--path, -p	string	.	Repository path

Example:

praisonai standardise redo

Workflow Example

# 1. Check current state
praisonai standardise check

# 2. Create checkpoint before changes
praisonai standardise checkpoint -m "Before standardisation"

# 3. Generate missing examples with AI
praisonai standardise ai guardrails --type examples --apply --verify

# 4. If something went wrong, undo
praisonai standardise undo

# 5. Generate report for documentation
praisonai standardise report --format markdown --output STANDARDISATION.md

Exit Codes

When using --ci mode:

Code	Meaning
0	No issues found
1	Issues found
2	Error running check

See Also

• Documentation Guide
• Examples Guide
• Contributing