flask-project-starter

Scaffold a production-ready Flask 3.x application with application factory, Blueprints, SQLAlchemy, JWT auth, and Gunicorn deployment.

Quality

80%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./backend-python/flask-project-starter/SKILL.md

Quality

Content

92%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a high-quality, comprehensive Flask scaffolding skill with excellent actionability and conciseness. The code examples are production-ready and follow Flask best practices. The main weakness is the monolithic structure - the skill would benefit from splitting detailed implementations into separate reference files while keeping SKILL.md as a leaner overview.

Suggestions

Consider splitting detailed code patterns (full route implementations, test examples, CLI commands) into separate reference files like PATTERNS.md or EXAMPLES.md, keeping SKILL.md as a concise overview with links

Add a brief validation checkpoint after the scaffold command to verify the directory structure was created correctly before proceeding to database initialization

Dimension	Reasoning	Score
Conciseness	The skill is dense with executable code and avoids explaining basic concepts Claude already knows. Every section provides actionable patterns without unnecessary preamble or explanation of what Flask, SQLAlchemy, or JWT are.	3 / 3
Actionability	Fully executable, copy-paste ready code throughout. Complete implementations for factory pattern, blueprints, models, schemas, routes, CLI commands, and tests. All code is production-quality Python, not pseudocode.	3 / 3
Workflow Clarity	Clear sequenced steps in 'First Steps After Scaffold' section with numbered workflow. Common commands section provides explicit validation steps (migrations, tests, lint). The scaffold command section shows the complete initialization sequence.	3 / 3
Progressive Disclosure	Content is well-organized with clear sections, but it's a monolithic document with ~400 lines of code. Some content (like full route implementations, test examples) could be split into referenced files for better navigation. No external file references are provided.	2 / 3
	Total	11 / 12 Passed

Description

67%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description excels at specificity and distinctiveness by naming exact technologies and versions (Flask 3.x, SQLAlchemy, JWT, Gunicorn). However, it lacks an explicit 'Use when...' clause which limits its completeness score, and could benefit from more natural user-facing trigger terms beyond technical jargon.

Suggestions

Add a 'Use when...' clause with trigger scenarios like 'Use when the user wants to create a new Flask project, start a Python web API, or needs a production-ready backend scaffold'

Include natural language variations users might say: 'Python web app', 'REST API', 'backend project', 'web server setup'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions and technologies: 'application factory, Blueprints, SQLAlchemy, JWT auth, and Gunicorn deployment' - these are all concrete, specific components that will be scaffolded.	3 / 3
Completeness	Clearly answers 'what' (scaffold a Flask app with specific components) but lacks an explicit 'Use when...' clause. The 'when' is only implied by the action verb 'Scaffold'.	2 / 3
Trigger Term Quality	Includes good technical terms like 'Flask', 'SQLAlchemy', 'JWT', 'Gunicorn', 'Blueprints' but misses common user variations like 'web app', 'API', 'backend', 'Python web framework', or 'REST API'.	2 / 3
Distinctiveness Conflict Risk	Very specific niche: Flask 3.x with a particular stack (SQLAlchemy, JWT, Gunicorn). Unlikely to conflict with Django, FastAPI, or general Python skills due to explicit Flask focus and version specification.	3 / 3
	Total	10 / 12 Passed

Validation

81%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (508 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	9 / 11 Passed

Repository: achreftlili/deep-dev-skills
Commit: 181fcbc

Reviewed: 4 months ago

Table of Contents

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